LIST OF THE COURSES

OF THE COMPUTER SCIENCE

CURRICULUM PROGRAM 2022

(TEACHING IN VIETNAMESE)

HIS101V: History of world civilization

General information about the course

Course name:				Course code: HIS101V
Vietnamese Name: History of world civilization English Name: World Civilizations History
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The subject provides students with basic and systematic knowledge about the history of formation, development process and some outstanding achievements in culture, science – technology… of prominent civilizations in the ancient and medieval period in the East such as Egypt, India, China and in the West such as Greece, Rome, Western European countries… helping students have basic knowledge about the history of development and progress of humanity.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic and systematic knowledge about the history of formation, development process and some outstanding achievements in culture, science – technology… of prominent civilizations of the period… helping students have basic knowledge about the history of development and progress of humanity.	CLO1: The subject provides students with basic and systematic knowledge about the history of formation, development process and some outstanding achievements in culture, science – technology… of prominent civilizations of the period… helping students have basic knowledge about the history of development and progress of humanity.	PLO2
	CLO2: Students understand the concepts of civilization, culture…
	CLO3: Understand the history of formation, development process and some outstanding achievements in culture, science and technology… of prominent civilizations through the ages…
	CLO4: Understand the value of the achievements of civilizations to the progress of humanity.
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate) ……	CLO5: Ensure presentation skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice thinking and writing skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills	PLO10, 12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete teamwork skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Vu Duong Ninh (2010), History of world civilization , Education Publishing House, Hanoi.

[2] Nguyen Thi Thanh Huyen (2018), World Civilization History Textbook , National Political Publishing House, Hanoi.

Reference

[3] Internet

[4] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO1,2,3,4,9	10%
II	Check course
1	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,9	10%
2	Personal article	Rubric 3	CLO1,2,3,4,6	10%
3	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,7,8	10%
4	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

HIS102V: Modern Times

General information about the course

Course name:				Course code: HIS102V
Vietnamese Name: Modern Times English name: Modern times
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The course covers world history from the discovery of the New World & the American Revolution to the end of the 20th century. Significant changes throughout history have been the result of trade, military and democracy. These events include the industrial revolution, European imperialism, trade and globalization, world wars, the rise of superpowers…

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The course covers world history from the discovery of the New World & the American Revolution to the end of the 20th century. Significant changes throughout history have resulted from trade, military and democracy. These events include the industrial revolution, European imperialism, trade and globalization, world wars, the rise of superpowers…	CLO1: The course covers world history from the discovery of the New World & the American Revolution to the end of the 20th century. Significant changes throughout history have resulted from trade, military, and democracy. These events include the industrial revolution, European imperialism, trade and globalization, world wars, the rise of superpowers, etc.	PLO2
	CLO2: Students understand the concepts of civilization, modernity, globalization…
	CLO3: Understand the history of formation, development process and some outstanding achievements of modern times
	CLO4: Understand the value of modern civilization for human progress.
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure presentation skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice thinking skills and writing skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills	PLO10, 12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete teamwork skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Arts and Culture: An Introduction to the Humanities , 4th Ed/ Janetta Benton and Robert DiYanni. – Boston: Prentice Hall, 2012. ISBN-13: 978-02058166062

[2] Perspectives from the Past: Primary Sources in Western Civilizations , 14th ed/ Brophy, Cole, Epstein, Robertson, Safley, eds.-Norton: New York, 2009. ISBN-13: 9780393265392

[3] Vu Duong Ninh (2010), History of world civilization , Education Publishing House, Hanoi.

[4] Nguyen Thi Thanh Huyen (2018), World Civilization History Textbook , National Political Publishing House, Hanoi.

Reference

[5] Worlds Together, Worlds Apart: A Companion Reader / Given Pomeranz & Mitchell, eds. – New York: Norton, 2011. ISBN: 9780393911602

[6] Discovering the Global Past: A Look at the Evidence , 2 Volumes, 3rd edition/ Weisner, Wheeler, Doeringer, Curtis. Eds. -Boston: Houghton Mifflin, 2007. ISBN-13: 9780618526383

[7] The World’s Religions: Worldviews and Contemporary Issues , 3rd Edition/ William A. Young. – Boston: Prentice Hall, 2010. ISBN-13: 9780205675111

[8] Civilization in the West , vol. 1/ Kishlansky, M., Geary, P., & O’Brien, P. – Boston: Penguin Academics, 2010. ISBN-13: 978020566472

[9] Internet

[10] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	10%
II	Check course
1	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,9	10%
2	Personal article	Rubric 3	CLO1,2,3,4,6	10%
3	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,7,8,9	10%
4	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

HUM101V: Essay Writing and Ideas

General information about the course

Course name:				Course code: HUM101V
Vietnamese Name: Essay Writing and Ideas English Name: Writing and Ideas
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 00
Number of assessment/discussion periods: 45
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

This course aims to help students develop their thinking skills, develop their ability to reason, evaluate and respond effectively to information presented. The course is not limited to written presentation and oral communication but focuses on the structure of arguments and how to avoid logical pitfalls. Information will be analyzed from news, public records, films, slides, transcripts and any other media sources and then put into a well-organized essay.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The course provides students with basic understanding of Essay Writing and Ideas	CLO1: Understand the definition of essay writing and ideas, explain the reasons for learning essay writing and ideas.	PLO2
	CLO2: Understand and analyze essay writing and brainstorming ideas
	CLO3: Understand and apply essay writing methods and brainstorm ideas to practice research writing.
Skill
CO2: (Discussion, presentation, speech, dialogue, debate)	CLO4: Have the skills to present, discuss and debate issues related to essay writing and ideas	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO5: Able to write essays and scientific reports in Vietnamese and English.	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO6: Participate in analyzing academic articles in TTU and local newspapers and magazines.	PLO10
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO7: Learn how to write essays and complete short scientific papers.	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO8: Have scientific knowledge and correct awareness of writing essays and ideas.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Nguyen Thien Giap (editor-in-chief), Doan Thien Thuat, Nguyen Minh Thuyet, 2008, Introduction to linguistics, Education Publishing House.

[2] Mai Ngoc Chu, Vu Duc Nghieu, Hoang Trong Phien, 1999, Linguistics and Vietnamese, Education Publishing House.

[3] Diep Quang Ban, 2005, Vietnamese Grammar, Education Publishing House.

[4] Do Huu Chau, 2005, Do Huu Chau selected works, Volume 2, Education Publishing House.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	– Diligent	Rubric 1	CLO1,2,3	5%
II	Check course
1	– Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4	20%
2	– Personal posts	Rubric 3	CLO1,2,3,4,5	5%
3	– Article (Group Project)	Rubric 4	CLO1,2,3,5,7	10%
4	– 60-minute multiple-choice/essay test	Rubric 5	CLO1,2,3,5,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,5,6,8	50%

ENGL108: Introduction to Cultural Studies

General information about the course

Course name:				Course code: ENGL108
Vietnamese Name: Introduction to Cultural Studies English title: Introduction to Cultural Studies
Courses: Compulsory ☒Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The subject provides students with basic theories of cultural studies, including: a system of basic concepts of culture, ways to identify culture, some specific cultural issues (yin-yang philosophy, symbolic culture, island culture, water culture…), some general features of Vietnamese and world culture, applied culture…

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic theories of cultural studies, including: a system of basic concepts of culture, ways to identify culture, some specific cultural issues (yin-yang philosophy, symbolic culture, island culture, water culture…), some general features of Vietnamese and world culture, applied culture…	CLO1: The subject provides students with basic theories of cultural studies, including: a system of basic concepts of culture, ways to identify culture, some specific cultural issues (yin-yang philosophy, symbolic culture, island culture, water culture…), some general features of Vietnamese and world culture, applied culture… CLO2: Students have basic knowledge of cultural studies. CLO3: Students have general knowledge about Vietnamese and world culture, applied culture… CLO4: Understand the value of culture for human progress.	PLO2
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure presentation skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice Thinking Skills and Writing Skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, consistent with course content requirements from seminars, short articles, and club practices.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Teamwork skills	PLO10, 12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete Teamwork Skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Tran Ngoc Them (2014), Theoretical and applied cultural studies issues , Ho Chi Minh City Culture – Literature Publishing House.

[2] Tran Ngoc Them (2006), Cultural studies and Vietnamese culture, University of Education Publishing House, Hanoi.

Reference

[3] Internet

[4] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	10%
2	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,7,8,9	10%
3	Personal article	Rubric 3	CLO1,2,3,4,6,9	10%
4	Article (Group Project)	Rubric 4	CLO1,2,3,4,7,8,9	10%
II	Check course
1	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

(Appendix – Assessment Rubric attached)

ART101: Contemporary Art

General information about the course

Course name:				Course code: ART101
Vietnamese Name: Contemporary Art English Name: Contemporary Art
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The course provides students with a fundamental understanding of art from its origins to the present day. Contemporary art in a world of global influence, cultural diversity and technology. The dynamic combination of materials, methods, concepts and themes continues to challenge the boundaries that were well underway in the 20th century. Contemporary art is part of a cultural dialogue that engages with larger contextual frameworks such as personal and cultural identity, family, community and nationality.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1 The course provides students with a fundamental understanding of art from its origins to the present day. Contemporary art in a world of global influence, cultural diversity and technology. The dynamic combination of materials, methods, concepts and themes continues to challenge the boundaries that were well underway in the 20th century.	CLO1: The course provides students with a basic understanding of art from its beginnings to the present day. Contemporary art in a world of global influence, cultural diversity and technology. Dynamic combination of materials, methods of expression. CLO2: Students understand the concepts of art, culture, contemporary art… CLO3: Understand the history, development process and some outstanding achievements in art. CLO4: Understand the value of contemporary art achievements.	PLO2
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure presentation skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice thinking and writing skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, consistent with course content requirements from seminars, short articles, and club practices.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Teamwork skills	PLO12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete teamwork skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility at work and strong connection with the community based on understanding from the subject – the value of connection.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Esaak, Shelley. “What is “Contemporary” Art?”. About.com. Accessed April 28, 2013.

[2] Sam Philips, (2021), ISMS – Understanding Modern Art , RA Magazine, Royal Academy of Arts Publishing House.

Reference

[3] Internet

[4] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	10%
2	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,7,9	10%
3	Personal article	Rubric 3	CLO1,2,3,4,6	10%
4	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,7,8,9	10%
II	Check course
1	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

(Appendix – Assessment Rubric attached)

CUL101: Vietnamese culture and some typical world cultures

General information about the course

Course name:				Course code: CUL101
Vietnamese Name: Vietnamese Culture and Some Typical World Cultures English Name: Vietnamese and other world classic cultures
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The course provides students with basic knowledge about Vietnamese culture (identity, value system, culture of some regions, culinary culture…) and some typical world cultures (Korea, Japan, China…) to help students understand the basics of Vietnamese culture and some typical world cultures.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with Vietnamese culture (identity, value system, culture of some regions, culinary culture…) and some typical world cultures (Korea, Japan, China…) to help students understand the basics of Vietnamese culture and some typical world cultures.	CLO1: The subject provides students with basic knowledge about Vietnamese culture (identity, value system, culture of some regions, culinary culture…) and some typical world cultures (Korea, Japan, China…) to help students have a basic understanding of Vietnamese culture and some typical world cultures. CLO2: Students have basic understanding of Vietnamese culture CLO3: Students have basic knowledge of some typical world cultures. CLO4: Understand the value of cultural achievements	PLO2
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure Presentation Skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice Thinking Skills and Writing Skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Teamwork skills	PLO12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete Teamwork Skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility at work and strong connection with the community based on understanding from the subject – the value of connection.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Tran Ngoc Them (2006), Cultural studies and Vietnamese culture, National University of Education Publishing House, Hanoi.

[2] Tran Ngoc Them (2014), Theoretical and applied cultural issues , Ho Chi Minh City Culture and Literature Publishing House.

Reference

[3] Internet

[4] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	10%
2	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4, 5,7,9	10%
3	Personal article	Rubric 3	CLO1,2,3,4,6,9	10%
4	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,78,9	10%
II	Check course
1	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

(Appendix – Assessment Rubric attached)

HUM102V: Culture and Literature

General information about the course

Course name:				Course code: HUM102V
Vietnamese Name: Culture and Literature English Name: Culture and Literature
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The subject provides students with basic knowledge about culture and literature, including: general theory of culture and literature; the role of culture and literature; basic knowledge about Vietnamese culture and some typical world cultures; some classic literary works of Vietnam and the world.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic knowledge about culture and literature, including: general theory of culture and literature; the role of culture and literature; basic knowledge about Vietnamese culture and some typical world cultures; some classic literary works of Vietnam and the world.	CLO1: Students have basic knowledge of culture and literature CLO2: Students understand the concepts of civilization, culture, literature… CLO3: Understand general theories about culture and literature; the role of culture and literature; basic knowledge about Vietnamese culture and some typical world cultures CLO4: Understand the value of some classic literary works of Vietnam and the world	PLO2
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure Presentation Skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO9
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice Thinking Skills and Writing Skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Teamwork skills	PLO12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete Teamwork Skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Tran Ngoc Them (2014), Theoretical and applied cultural studies issues, Ho Chi Minh City Culture – Literature Publishing House.

[2] Tran Ngoc Them (2006), Cultural studies and Vietnamese culture, National University of Education Publishing House

[3] Tran Dinh Su (2020), editor-in-chief, Brief History of Vietnamese Literature, Hanoi National University of Education Publishing House.

[4] Many authors, (2007), Brief history of world literature, Literature Publishing House.

[5] Classic literary works of Vietnam and the world.

Reference

[6] Internet

[7] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	5%
II	Check course
1	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,7,8,9	20%
2	Personal article	Rubric 3	CLO1,2,3,4,6	5%
3	Article (Group Project)	Rubric 4	CLO1,2,3,4,6, 7,8	10%
4	60-minute multiple-choice/essay test	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	-90-minute multiple-choice/essay test -Personal article	Rubric 5	CLO1,2,3,4,6	50%

(Appendix – Assessment Rubric attached)

MGT102: Leadership and Communication

General information about the course

Course name:				Course code: MGT102
Vietnamese Name: The Art of Leadership and Communication English Name: Leadership and Communication
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The course provides students with a basic and systematic knowledge of historical, theoretical and practical perspectives on leadership (traits, skills, styles, situations, contingencies, pathways, transformational leadership and team leadership) and communication (communication elements, communication status of leaders; using social status and communication status to communicate effectively in a leadership role). The course will also guide students to apply these theories to practical problems.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The course provides students with basic and systematic knowledge of historical, theoretical and practical perspectives on leadership (traits, skills, styles, situations, contingencies, pathways, transformational leadership and team leadership) and communication (communication elements, communication status of leaders; using social status and communication status to communicate effectively in a leadership role).	CLO1: The course provides students with basic and systematic knowledge of historical, theoretical and practical perspectives on leadership and communication. CLO2: Students understand the concepts of leadership and communication. CLO3: Understand the system of historical, theoretical and practical perspectives on leadership and communication. CLO4 : Understand the importance of mastering knowledge about leadership and communication to be able to apply it well in life.	PLO2
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure Presentation Skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice Thinking Skills and Writing Skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Teamwork skills	PLO12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete Teamwork Skills	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Northouse, PG (2016). Leadership: Theory and Practice (7 Edition)

[2] Daft, R.L., (2009). Principles of Management . India: Akash Press Vogt, E.E., Brown, J., & Isaacs, D. (2003). Online services

[3] Ao Thu Hoai (2018), Leadership Art Textbook , Information & Communication Publishing House.

[4] Do Huu Chau, Pragmatics section (2008), Pragmatics section “Do Huu Chau selected works”, Volume 2, Education Publishing House.

Reference

[5] Internet

[6] Other documents (latest updates on media platforms)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO9	10%
2	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5,9	10%
3	Personal article	Rubric 3	CLO1,2,3,4,6,9	10%
4	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,7,8,9	10%
II	Check course
1	Midterm test multiple choice/essay	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6	50%

(Appendix – Assessment Rubric attached)

HUM205: Language and Vietnamese

General information about the course

Course name:				Course code: HUM205
Vietnamese Name: Language and Vietnamese English Name: Language and Vietnamese
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge

Brief description of course content

The subject provides students with basic understanding of The subject provides students with basic understanding of language in general (origin, nature, function…) and Vietnamese with basic characteristics: phonetics, vocabulary, semantics, grammar and pragmatics.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic understanding of language in general (origin, nature, function…) and Vietnamese with its basic characteristics: phonetics, vocabulary, semantics, grammar and pragmatics.	CLO1: Students have basic knowledge of general languages.	PLO2
	CLO2: Students understand the basic concepts of linguistics
	CLO3: Understand general theories about language in general (origin, nature, function…)
	CLO4: Students understand and grasp the basic characteristics of Vietnamese: phonetics, vocabulary, semantics, grammar and pragmatics.
Skill
CO2: Seminar (Discussion, presentation, discourse, dialogue, debate)	CLO5: Ensure Presentation Skills with basic requirements: – Duration – How to layout a presentation – Presentation content – Way of speaking – way of presenting – way of presenting (voice, facial expression, eyes, movements…) – Illustrative video * Have the ability to analyze and identify problems from the subject * Have skills in searching for documents and self-study.	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO6: Practice Thinking Skills and Writing Skills with basic requirements: – Duration – How to layout the article – Article content (ideas – outline) – Writing style: written language * Have the ability to analyze and identify problems from the subject * Have skills in searching for documents and self-study.	PLO10
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO7: Acquire analytical skills, decision-making and problem-solving skills – Have teamwork skills (discussion and presentation)	PLO12
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO8: Complete Teamwork Skills – Have teamwork skills (discussion and presentation)	PLO12
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO9: Sense of responsibility in work and strong connection with the community based on understanding from the subject – the value of connection in the process of human development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Nguyen Thien Giap (editor-in-chief), Doan Thien Thuat, Nguyen Minh Thuyet, 2008, Introduction to linguistics, Education Publishing House.

[2] Mai Ngoc Chu, Vu Duc Nghieu, Hoang Trong Phien, 1999, Linguistics and Vietnamese, Education Publishing House.

[3] Diep Quang Ban, 2005, Vietnamese Grammar, Education Publishing House.

[4] Do Huu Chau, 2005, Do Huu Chau selected works, Volume 2, Education Publishing House.

Reference

[5] Internet;

[6] Other documents (latest updates on media platforms).

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
	Diligence	Rubric 1	CLO9	5%
II	Check course
	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4,5	20%
	Personal article	Rubric 3	CLO1,2,3,4,6	5%
	Article (Group Project)	Rubric 4	CLO1,2,3,4,6,7,8	10%
	60-minute multiple-choice/essay test	Rubric 5	CLO1,2,3,4,6	10%
III	Final exam
	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,4,6,9	50%

(Appendix – Assessment Rubric attached)

ENV101: People and the Environment

General information about the course

Course name:				Course code: ENV101
Vietnamese Name: People and the Environment English Name: Human and Environment
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Nguyen Thanh Dien	0763550172	dien.nguyenthanh@ttu.edu.vn	In charge

Brief description of course content

The subject provides basic knowledge to build a correct attitude in perceiving the organic relationships between the development needs of human society and the exploitation and use of natural resources. The subject aims to educate people to be aware of protecting the living environment and fighting against pollution problems. The subject provides students with an understanding of global environmental problems and solutions. In addition, practical activities in class are integrated into the lectures to make them more vivid and practical.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Have basic knowledge of the relationship between the environment and humans	CLO1: Apply basic principles in environmental science to explain the relationship between humans and the environment; thereby, raising awareness in environmental protection and sustainable development.	PLO1
	CLO2: Explain environmental change, population change, and the impact between humans and the environment globally.
	CLO3: Describe current environmental problems in the world in general and in Vietnam in particular.
Skill
CO2: Ability to apply environmental knowledge to work and life	CLO4: Able to present, discuss and debate environmental issues in Vietnam and the world	PLO10
	CLO5: Ability to analyze and process information on environmental issues.
	CLO6: Participate in environmental protection activities at school and locality
	CLO7: Write a small project on environmental protection
Self-control and responsibility
CO3: Recognize issues according to ethical standards and professional requirements to adapt to social employment needs and integrate into the international working environment.	CLO8: Correct perception of the relationship between environment, humans and climate.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Pham Hong Minh, 2011, Environmental Health , Ho Chi Minh City University of Medicine and Pharmacy Publishing House.

Reference

[2] Robert H.Friis, 2019, Essentials of Environmental Health , Third Edition, Apha Press.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment: Diligence	Rubric 1	CLO6,7,8	10%
2	Presentation/Discussion	Rubric 2	CLO1,2,3,4,5	20%
3	Midterm Assessment: Multiple Choice	According to the answer	CLO1,2,3,5	20%
4	Final Assessment: Multiple Choice	According to the answer	CLO1,2,3,5	50%

(Appendix 1 – Assessment Rubric attached)

ENV102: Climate Change

General information about the course

Course name:				Course code: ENV102
Vietnamese Name: Climate Change English Name: Climate Change
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : None
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Nguyen Thanh Dien	0763550172	dien.nguyenthanh@ttu.edu.vn	In charge

Brief description of course content

– The subject aims to provide students with basic knowledge about the Earth’s climate patterns, causes of climate change, challenges and opportunities of climate change, impacts of climate change on resources and the environment, and how humans respond to climate change.

– The course provides knowledge about the process by which global, national, and regional organizations develop climate change response plans.

– The course describes how countries educate climate change knowledge to students.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The course provides students with basic understanding of Climate Change.	CLO1: Understand the definition of climate change and explain the causes of climate change.	PLO1
	CLO2: Understand and analyze the consequences and impacts of climate change on resources and the environment.
	CLO3: Understand and identify ways (solutions) of human response to climate change at global and local scales to ensure sustainable development goals.
Skill
CO2: (Discussion, presentation, speech, dialogue, debate)	CLO4: Have the skills to present, discuss and debate environmental issues in Vietnam and the world.	PLO10
CO3: Writing (Write essays, reports, midterms, and final papers)	CLO5: Ability to write essays and scientific reports in Vietnamese and English.
CO4: Service learning Course activities are associated with solving social problems, suitable for course content requirements from seminars, short articles, club practices, etc.	CLO6: Participate in environmental protection activities at TTU and locally.
CO5: Group Project The topic given by the teacher is appropriate to the subject content.	CLO7: Learn how to write a mini project about the environment.
Self-control and responsibility
CO6: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development	CLO8: Have scientific knowledge and correct awareness of the environment, people and climate.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Hardy, J.T., 2003, Climate Change: Causes, Effects and Solutions. John Wiley & Sons, Chichester.

[2] Andrew Dessler, 2016, Introduction to Modern Climate Change, Cambridge University Press; 2nd edition.

[3] Gates, B., 2021, How to Avoid a Climate Disaster: The Solutions We Have and the
Breakthroughs We Need, Alfred A. Knopf, New York.

Reference

[4] The Intergovernmental Panel on Climate Change (IPCC): https://www.ipcc.ch/

[5] United Nations and Climate Change: https://www.un.org/en/climatechange/what-isclimate-change

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Rating (up to 10%)
1	Diligence	Rubric 1	CLO6,8	5%
II	Check course
1	Presentation/discussion/dialogue	Rubric 2	CLO1,2,3,4	10%
2	Personal article	Rubric 3	CLO1,2,3,4,5	5%
3	Article (Group Project)	Rubric 4	CLO1,2,3,5,7	10%
4	60-minute multiple-choice/essay test	Rubric 5	CLO1,2,3,5,6	10%
III	Final exam
1	– 90-minute multiple-choice/essay test – Personal posts	Rubric 5	CLO1,2,3,5,6,8	60%

(Appendix – Assessment Rubric attached)

ENTR101: Creative Entrepreneurship

General information about the course

Course name:				Course code: ENTR101
Vietnamese Name: Creative Startup English Name: Entrepreneurship
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 10
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Economics and Business Administration

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Nguyen Vu Hieu Trung	0902989411	trung.nguyen@ttu.edu.vn	In charge
2	MSc. Tran Vu Phong	–	phong.vu@ttu.edu.vn	Join

Brief description of course content

The Creative Entrepreneurship course equips students with basic knowledge and practical skills in entrepreneurship, especially creative thinking and the ability to build a suitable business model in the modern economic context. Students will learn about the concepts, benefits and challenges of creative entrepreneurship, combined with tools and methods such as Design Thinking, market research, building a Business Model Canvas, marketing strategy and financial management. The course also guides students in planning implementation, project management and pitching skills to raise capital from investors.

Through hands-on activities, group work and real-life startup projects, the course helps students from various disciplines develop interdisciplinary skills, innovative thinking, and the ability to apply knowledge to solve real-world problems. At the end of the course, students will be able to develop and present a complete business idea, creating a foundation for future startup projects.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Apply basic knowledge of entrepreneurship, innovation and business models to develop business ideas.	CLO1: Present basic concepts of entrepreneurship, characteristics of creative entrepreneurship and its role in the modern economy.	PLO2
	CLO2: Analyze market factors, target customers and build a suitable business model.
	CLO3: Apply market research methods and tools (SWOT, PESTEL) to develop business ideas
Skill
CO2: Develop skills in building business strategies, marketing, financial management and fundraising to implement startup projects.	CLO4: Design and implement basic marketing strategies (4Ps, 7Ps) to promote products or services	PLO10,12
	CLO5: Perform financial planning steps, calculate costs, revenue and predict profits in startups.
	CLO6: Practice pitching skills to convince investors and stakeholders
Self-control and responsibility
CO3: Demonstrate teamwork spirit, critical thinking and sense of responsibility in the process of developing and implementing startup ideas	CLO7: Demonstrate the ability to work in a team and coordinate effectively among members to complete a startup project.	PLO12,14
	CLO8: Demonstrate initiative, creativity and responsibility in developing ideas and solving practical problems.	PLO14
	CLO9: Evaluate and criticize startup ideas objectively, with a spirit of progress and learning.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] The Harvard Business Review Entrepreneur’s Handbook : Everything You Need to Launch and Grow Your New Business

[2] Entrepreneurship, Ninth Edition by Hisrich, Robert D .

Reference:

[3] Entrepreneurial thinking Joel Comm , John Rampton; Ha Tien Hung translated, Hanoi Lao Dong 2018

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight (%)
1	Participate in class activities and group discussions	Roll call, observe participation and contribution (Rubric 1,2 and 6)	CLO1.7	10%
2	Group assignment: Market analysis and building a simple business model	Market analysis report and persona. Complete Business Model Canvas (BMC) (Rubric 4)	CLO2,4,5	20%
3	Group Presentation (Startup Project Pitching)	Group presentation and debate (Rubric 4)	CLO6,8,9	20%
4	Final Project Report: Idea Implementation Plan	Project report and finished product (Rubric 4)	CLO3,4,5,7	25%
5	Final exam: Multiple choice and essay	Comprehensive knowledge test (Rubric 5)	CLO1,2,3	25%

PRFN01: Personal financial management

General information about the course

Course name:				Course code: PRFN01
Vietnamese Name: Personal Financial Management English Name: Personal Finance Management
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 03
Number of other activities: 00
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Dang Huu Phuoc	0989777685	phuoc.dangh@ttu.edu.vn	In charge
2	MSc. Nguyen Dieu Minh Tam	0356332668	tam.nguyenmd@ttu.edu.vn	Join

Brief description of course content

The course provides learners with knowledge and tools to enable them to plan their finances; build financial plans; analyze and make important financial decisions related to spending, saving, investing and risk management. It helps learners proactively make financial decisions, as well as develop their careers to become professional financial consultants at financial institutions.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand personal finance concepts related to saving, borrowing, investing, and risk management.	CLO1: Understand different forms of personal finance and how they relate to saving, borrowing, investing and risk management	PLO2
	CLO2: Have skills and positive behavior in building personal credit history for customers and enhancing customer reputation and image in accessing and using financial instruments and products.
Skill
CO2: Apply appropriate and accurate financial concepts and tools to assess, evaluate and make personal financial decisions.	CLO3: Apply financial knowledge to financial planning and personal financial decision making.	PLO8
Self-control and responsibility
CO3: Enhance independence, proactive attitude, positivity, enthusiasm, creativity and innovation.	CLO4: Have the right awareness and skills in assessing the importance of saving, spending and financial planning for customers and know how to maximize financial resources.	PLO8, PLO15
	CLO5: Make decisions based on information analysis and evaluation.

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Jack R. Kapoor, Les R. Dlabay, Hughes Robert J. (2012), Personal Finance , McGrawn-Hill/Irwin.

Reference

[2] E. Thomas Garman, Raymond E. Forgue (2015), Personal finance , Cengage Learning.

[3] Bach, D. (2004). The Automatic Millionaire . New York: Broadway Books.

[4] Personal Finance for Vietnamese – Lam Minh Chanh

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment: Diligence	Rubric 1	CLO4	10%
2	Individual/group assignment assessment	Rubric 6	CLO4,5	20%
3	Midterm Assessment: Multiple Choice/ Essay	Rubric 2	CLO1,2,3	20%
4	Final Assessment: Multiple Choice/ Essay	Rubric 2	CLO1,2,3	50%

(Appendix 1 – Assessment Rubric attached)

MACL108: Marxist-Leninist Philosophy

General information about the course

Course name:				Course code: MACL108
Vietnamese name: Marxist-Leninist philosophy English Name: Marxist-Leninist Philosophy
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	MSc. Nguyen Thi Lich	0988568235	lich.nguyen@ttu.edu.vn	Join

Brief description of course content

Marxist-Leninist philosophy is one of the three components of Marxism-Leninism. The course content consists of 03 chapters, explaining general issues related to the existence and development of the world in general and the existence and development of human society in particular, equipping learners with a correct worldview, a positive outlook on life, as well as a dialectical and scientific methodology, in order to effectively solve problems arising in practice. The course is also the basis for students to well absorb Political Theory subjects, as well as other scientific subjects.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic and systematic knowledge and explains general issues related to the existence and development of the world in general, and the existence and development of human society in particular, equipping students with a correct worldview, a positive outlook on life, as well as a dialectical and scientific methodology, in order to effectively solve problems arising in practice.	CLO1: Students have basic knowledge of general issues related to the existence and development of the world in general, and the existence and development of human society in particular.	PLO2
	CLO2: Students understand philosophical concepts…
	CLO3: Students have a correct worldview, positive outlook on life, as well as dialectical and scientific methodology.
	CLO4: Understand the value of philosophy in practical life.
Skill
CO2: Practice teamwork skills, self-study, exploit learning materials, and search for information under the guidance of instructors. Apply learned knowledge to perceive some problems within the scope of the profession.	CLO5: Acquire skills in teamwork, self-study, exploiting learning materials, and searching for information. Teamwork skills.	PLO9, PLO12
	CLO6: Acquire analytical skills, decision-making and problem-solving skills.	PLO8
Self-control and responsibility
CO3: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development.	CLO7: Demonstrate a positive attitude towards the scientific nature of the subject. Demonstrate a spirit of lifelong learning.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2014), Textbook Basic principles of Marxism – Leninism , National Political Publishing House, Hanoi.

Assessment of learning outcomes

I	Instructor Reviews
1	– Diligent	Rubric 1	CLO1, 2, 3, 4	10%
2	– Group exercise	Rubric 2	CLO1, 5, 6	10%
II	Course Test (up to 40%)
1	– 60-minute essay/multiple choice midterm test	Rubric 4	CLO1, 2, 3, 4, 6	10%
2	– Group presentation	Rubric 3	CLO1, 4, 5, 6	10%
III	Final exam (minimum 50%)
1	– 90-minute final essay/multiple choice test	Rubric 4	CLO1, 2, 3, 4, 6, 7	60%

(Appendix 1 – Assessment Rubric attached)

MACL109: Marxist-Leninist Political Economy

General information about the course

Course name:				Course code: MACL109
Vietnamese name: Marxist-Leninist political economy English name: Political economics of Marxism – Leninism
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : Marxist-Leninist Philosophy
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	MSc. Nguyen Thi Lich	0988568235	lich.nguyen@ttu.edu.vn	Join

Brief description of course content

Based on the subject’s objectives, the content of the Marxist-Leninist political economy program is structured into 6 chapters. It helps students grasp the most basic issues about goods, markets; surplus value in the commodity economy, industrialization, modernization, and integration of Vietnam.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: The subject provides students with basic knowledge about the nature of goods and commodity production; issues related to the market and the role of market participants in the commodity economy. Marxist-Leninist theory on surplus value, the process of creating surplus value, the process of capital accumulation, the nature of competition and monopoly, the socialist-oriented market economy in Vietnam, industrialization, modernization as well as the process of international economic integration of Vietnam.	CLO1: Students have basic knowledge of general issues related to economics, commodity production, markets, economic integration and industrialization – modernization of the country.	PLO2
	CLO2: Students understand the concepts of political economy…
	CLO3: Students have the right perspective and scientific method when approaching content.
	CLO4: Understand the value of Marxist-Leninist political economy in practice.
Skill
CO2: Practice teamwork skills, self-study, exploit learning materials, and search for information under the guidance of instructors. Apply learned knowledge to perceive some problems within the scope of the profession.	CLO5: Acquire skills in teamwork, self-study, exploiting learning materials, and searching for information. Teamwork skills.	PLO9, PLO12
	CLO6: Acquire analytical skills, decision-making and problem-solving skills.	PLO8
Self-control and responsibility
CO3: Responsibility, commitment to achieving common construction goals with the highest possible quality, discipline and self-motivation towards work and personal development.	CLO7: Demonstrate a positive attitude towards the scientific nature of the subject. Demonstrate a spirit of lifelong learning.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2014), Textbook Basic principles of Marxism – Leninism , National Political Publishing House, Hanoi.

Assessment of learning outcomes

I	Instructor Reviews
	– Diligent	Rubric 1	CLO1,2,3,4	10%
	– Group exercise	Rubric 2	CLO1,5,6	10%
II	Course Test (up to 40%)
	– 60-minute essay/multiple choice midterm test	Rubric 4	CLO1,2,3,4,6	10%
	– Group presentation	Rubric 3	CLO1,4,5,6	10%
III	Final exam (minimum 50%)
	– 75-minute final essay/multiple choice test	Rubric 4	CLO1,2,3,4,6,7	60%

(Appendix 1 – Assessment Rubric attached)

MACL104: Ho Chi Minh Thought

General information about the course

Course name:				Course code: MACL104
Vietnamese Name: Ho Chi Minh Thought English Name: Ho Chi Minh Thought
Courses: ☒ Required ⬜ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : Marxist-Leninist Philosophy, Marxist-Leninist Political Economy, Scientific Socialism.
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	MSc. Nguyen Thi Lich	0988568235	lich.nguyen@ttu.edu.vn	Join

Brief description of course content

Based on the subject’s purpose, the Ho Chi Minh Thought program is structured into 6 chapters, discussing the concept of Ho Chi Minh Thought, its origin, stages of development, objects, research tasks and basic ideological contents of Ho Chi Minh.

The subject of Ho Chi Minh Thought is closely related to the subjects of the Revolutionary Path of the Communist Party of Vietnam and the Basic Principles of Marxism-Leninism. Because the Party’s path is the creative application and development of Marxism-Leninism and Ho Chi Minh Thought into the reality of the Vietnamese revolution.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Identify basic and core knowledge about Knowledge about the process of formation and development of basic content of Ho Chi Minh’s ideology.	CLO1: Students know the concepts: nation and national liberation revolution; socialism and the transitional path to socialism; the Communist Party of Vietnam; national solidarity and international solidarity; democracy and building a state of the people, by the people, for the people; culture, ethics and building new people according to Ho Chi Minh’s thought.	PLO2
	CLO2: Students know how to apply theory to practice, solve theoretical and practical problems of the nation and humanity.
	CLO3: Students systematically understand the ideological foundation of the Communist Party of Vietnam in the process of leading our country’s revolution from the national, people’s democratic revolution to the socialist revolution.
Skill
CO2: Identify basic and core knowledge about the process of formation and development of basic content of Ho Chi Minh’s ideology.	CLO4: Achieve teamwork skills, self-study, exploiting learning materials, searching for information.	PLO9, PLO12
	CLO5: Acquire analytical skills, decision-making and problem-solving skills.	PLO8
Self-control and responsibility
CO3: Believe in the path to socialism in our country, enhance national pride and affection for the Party and President Ho Chi Minh; establish a sense of responsibility and a positive attitude to participate in building and defending the Fatherland.	CLO6: Demonstrate a positive attitude towards the scientific nature of the subject. Demonstrate determination to strive to become a person with moral qualities, a pure lifestyle, ideals, and a working class stance.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2013), Ho Chi Minh Thought (For undergraduates not majoring in Political Theory) , National Political Publishing House, Hanoi.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	– Diligent	Rubric 1	CLO1, 2, 3	10%
2	– Group exercise	Rubric 2	CLO2, 4, 5	10%
II	Course Test (up to 40%)
1	– 60-minute essay/multiple choice midterm test	Rubric 4	CLO1, 2, 3, 5	10%
2	– Group presentation	Rubric 3	CLO2,4,5	10%
III	Final exam (minimum 50%)
1	– 75-minute final essay/multiple choice test	Rubric 4	CLO1,2,3,5,6	60%

(Appendix 1 – Assessment Rubric attached)

MACL110: Scientific Socialism

General information about the course

Course name:				Course code: MACL110
Vietnamese name: Scientific socialism English Name: Science Socialism
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : Marxist-Leninist Philosophy.
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	MSc. Nguyen Thi Lich	0988568235	lich.nguyen@ttu.edu.vn	Join

Brief description of course content

Based on the subject’s purpose, the content of the scientific socialism program is structured into 7 chapters. Providing students with scientific theoretical bases to understand and have revolutionary faith in the path of building and developing the country in the current transitional period to socialism in Vietnam.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Identify basic and core knowledge about scientific socialism and common political and social issues in the process of building socialism in Vietnam today.	CLO1: Students know the concepts: What is scientific socialism, the process of formation and development of scientific socialism; the historical mission of the working class; socialism and the transition period to socialism; socialist democracy and the socialist state; social structure – class and class alliance, strata in the transition period to socialism; ethnic and religious issues, family issues in the transition period to socialism.	PLO2
	CLO2: Students know how to apply theory to practice, correctly implementing the policies of the Party and State.
	CLO3: Students have political courage and have faith in and strictly follow the Party’s policies and leadership in the process of building the country along the path of socialism.
Skill
CO2: From basic knowledge, core core of social science, learners are able to ability to apply learned knowledge assessing and reviewing the country’s socio-political issues related to socialism and the path to socialism in Vietnam.	CLO4: Achieve teamwork skills, self-study, exploiting learning materials, searching for information. Teamwork skills.	PLO9, PLO12
	CLO5: Acquire analytical skills, decision-making and problem-solving skills.	PLO8
Self-control and responsibility
CO3: Have strong political will. Have faith in the goals and success of socialism in Vietnam. Strictly follow the Party’s policies and leadership in the process of building the country along the path of socialism.	CLO6: Demonstrate a positive attitude towards the scientific nature of the subject. Demonstrate a spirit of lifelong learning.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2014), Textbook Basic principles of Marxism – Leninism , National Political Publishing House, Hanoi.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	– Diligent	Rubric 1	CLO1, 2, 3	10%
2	– Group exercise	Rubric 2	CLO2, 4, 5	10%
II	Course Test (up to 40%)
1	– 60-minute essay/multiple choice midterm test	Rubric 4	CLO1, 2, 3, 5	10%
2	– Group presentation	Rubric 3	CLO2, 4, 5	10%
III	Final exam (minimum 50%)
1	– 90-minute final essay/multiple choice test	Rubric 4	CLO1, 2, 3, 5, 6	60%

(Appendix 1 – Assessment Rubric attached)

MACL111: History of the Communist Party of Vietnam

General information about the course

Course name:				Course code: MACL111
Vietnamese Name: History of the Communist Party of Vietnam English title: History of Communist Party of Vietnam
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of discussion/evaluation periods: 00
Number of other activities: 00
Prerequisite courses *(if any)* : Marxist-Leninist philosophy, Scientific socialism, Marxist-Leninist political economy, Ho Chi Minh thought.
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	MSc. Nguyen Thi Lich	0988568235	lich.nguyen@ttu.edu.vn	Join

Brief description of course content

The subject History of the Communist Party of Vietnam basically studies the process of formation and development of the Party and the contents of the Party’s guidelines set forth in the process of leading the Vietnamese revolution from 1930 to the present. Therefore, the main content of the subject is to provide students with basic and systematic understanding of the Party’s viewpoints, guidelines and policies, especially in the period of renovation.

The subject History of the Communist Party of Vietnam has a close relationship with the subject Basic principles of Marxism-Leninism and Ho Chi Minh Thought. Because the Party’s line is the creative application and development of Marxism-Leninism and Ho Chi Minh Thought into the practice of the Vietnamese revolution.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provides basic content on the revolutionary line of the Communist Party of Vietnam.	CLO1: Students know the content of the Party’s guidelines during the renovation period in some basic areas of social life to serve life and work.	PLO2
	CLO2: Students know how to apply theory to practice, solve theoretical and practical problems of the nation and humanity.
	CLO3: Students systematically understand the ideological foundation of the Communist Party of Vietnam in the process of leading our country’s revolution from the national, people’s democratic revolution to the socialist revolution.
Skill
CO2: Apply specialized knowledge to proactively and positively solve economic, political, cultural and social issues according to the Party’s guidelines and policies and the State’s laws.	CLO4: Achieve teamwork skills, self-study, exploit learning materials, and search for information	PLO9, PLO12
	CLO5: Acquire analytical skills, decision-making and problem-solving skills. Have the ability to think logically, the ability to apply knowledge of the subject to real life, work and society. Ability to respond to social requirements in the process of innovation and international economic integration.	PLO8
Self-control and responsibility
CO3: Believe in the path to socialism in our country, enhance national pride and affection for the Party and President Ho Chi Minh; establish a sense of responsibility and a positive attitude to participate in building and defending the Fatherland.	CLO6: Demonstrate a positive attitude towards the scientific nature of the subject. Determined to strive to become a person with moral qualities, a pure lifestyle, ideals, and a working class stance.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2021), Revolutionary Line of the Communist Party of Vietnam Textbook , National Political Publishing House, Hanoi.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	– Diligent	Rubric 1	CLO1, 2, 3	10%
2	– Group exercise	Rubric 2	CLO2, 4, 5	10%
II	Course Test (up to 40%)
1	– 60-minute essay/multiple choice midterm test	Rubric 4	CLO1, 2, 3, 5	10%
2	– Group presentation	Rubric 3	CLO2, 4, 5	10%
III	Final exam (minimum 50%)
1	– Final essay test/ 75-minute multiple-choice test	Rubric 4	CLO1, 2, 3, 5, 6	60%

(Appendix 1 – Assessment Rubric attached)

LAW102: General Law

General information about the course

Course name:				Course code: LAW102
Vietnamese Name: General Law English Name: Fundamentals of Law
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities and Liberal Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Associate Professor, Dr. Mai Thi Hao Yen	0911336529	yen.mai@ttu.edu.vn	In charge
2	Dr. Nguyen Van Vi	0934188567	nguyenvanvi67@gmail.com	Join

Brief description of course content

The General Law course provides basic and systematic knowledge of law and some basic branches of law in the Vietnamese legal system to raise legal awareness and form voluntary law-abiding behavior for learners.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic concepts of the subject	CLO1: Understand the basic concepts of state and law: concept, origin, nature, form, types of state and law in the world	PLO2
	CLO2: Understand the basic categories of law: legal norms, legal relations, legal violations, socialist legal system, legal awareness	PLO2
Skill
CO2: Know how to apply theoretical knowledge to consider and evaluate legal issues arising in practice.	CLO3: Know how to apply general theoretical knowledge about the state and law to determine legal status (rights and obligations of individuals and organizations) and to consider and evaluate the activities of individuals and organizations according to the provisions of law.	PLO9
	CLO4: Know how to apply theoretical knowledge of legal norms, legal relationships, and legal violations to consider and evaluate whether a specific law, a specific legal relationship, or a specific legal act in practice is right or wrong according to the provisions of the law.
Self-control and responsibility
CO3: Be aware of respecting and strictly implementing the laws of the State, the rules and regulations of the School.	CLO5: Be aware of living and working according to the law, gradually forming behaviors in accordance with the law in all areas of social life.	PLO15
	CLO6: Be aware of fighting against law violations in schools and in society.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ministry of Education and Training (2010), General Law . Internal circulation.

Reference

[2] National Assembly, (2015). Civil Code 2015. National Political Publishing House.

[3] National Assembly, (2015). Civil Procedure Code 2015. National Political Publishing House.

[4] National Assembly, (2015). Criminal Procedure Code 2015. National Political Publishing House.

[5] National Assembly, (2017). Penal Code amended in 2017. National Political Publishing House.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	– Diligence + Returning homework	Rubric 1 + Return	CLO1,2	10%
II	Course Test (up to 40%)
1	– Midterm test (essay)	Rubric 3	CLO3,4	20%
2	– Draw a mind map	Rubric 2	CLO1,2,5,6	20%
III	Final exam (minimum 50%)
1	– Final exam (essay)	Rubric 3	CLO1	50%

(Appendix 1 – Assessment Rubric attached)

INF102: Introduction to Computer Science

General information about the course

Course name:				Course code: INF102
Vietnamese name: General Information Technology English Name: Introduction to Informatics
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 01	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 45
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	CN. Doan Ngoc Nhat Minh	091 311 4960	minh.doan@ttu.edu.vn	Teaching Assistant

Brief description of course content

General Computer Science course provides students with basic computer skills. Topics include: overview of computer systems, searching and using the Internet, online learning, information security, computer protection, and office skills with Microsoft Office.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand basic concepts of computers, networks and the Internet, effectively use Microsoft Office and Google Drive software in work and study.	CLO1: Understanding the basic concepts of computers, computer networks and the Internet helps students use the Internet effectively and safely.	PLO3-6
	CLO2: Effectively use Microsoft Office software including Powerpoint and Word in work and study.	PLO3-6
	CLO3: Effectively use Google Drive software in collaborative work.	PLO3-6
Skill
CO2: practice problem solving skills.	CLO4: Have problem solving and report writing skills.	PLO8, 12
Level of autonomy and responsibility
CO3: Sense of responsibility.	CLO5: Demonstrate responsibility and seriousness in studying.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Many authors. General Information Technology Textbook . Pedagogical University Publishing House.

[2] Microsoft Office: https://products.office.com/vi-VN/

[3] Connie Morrison , Dolores Wells , Lisa Ruffolo (2014). Computer Literacy BASICS: A Comprehensive Guide to IC3 . Cengage Learning.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO5	5%
2	Practice.	Rubric AM9	CLO2, 3	10%
3	Homework.	Rubric AM2a	CLO2, 3, 4	5%
4	Midterm Test: Multiple Choice.	Multiple choice scale	CLO1, 2, 3, 4	30%
II	Final assessment
1	Multiple choice test.	Multiple choice scale	CLO1, 2, 3, 4	50%

(Appendix – Assessment Rubric attached)

MACL1051: Physical Education 1

General information about the course

Course name:				Course code: MACL1051
Vietnamese Name: Physical Education 1 English Name: Physical Education 1
Courses: ☒ Compulsory ◻ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 01
Number of theoretical credits: 00	Number of practice credits: 01		Number of internship credits: 00
Number of theory periods: 00		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 15
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Department of course management *(if any)* : Faculty of Humanities & General Education

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Ms. Nguyen Thi Hong Van	0978250950	van.nguyen@ttu.edu.vn	In charge

Brief description of course content

This course provides learners with basic knowledge of Physical Education, as well as knowledge of team formation and general development exercises. Through this, learners will know how to organize, manage a group and be able to compose general development exercises.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understanding of basic rules and regulations of Athletics.	CLO1: Understand the basic rules and regulations of Athletics.	PLO2
	CLO2: Master the basic methods and techniques of Athletics such as Team formation, sprinting, endurance running, relay running, etc.	PLO2
	CLO3: Master the movements of the basic morning exercise routine.	PLO2
CO2: Understand the history and development of Athletics and its role in health and fitness.	CLO4: Present knowledge about the history and development of Athletics as well as understanding of its impact on health and fitness.	PLO2
Skill
CO3: Develop basic skills in Athletics techniques and skills	CLO5: Perform basic techniques and skills of Athletics such as Team formation, sprinting, endurance running, relay running, etc.	PLO12
	CLO6: Perform basic morning exercises and create morning exercises (with sticks).	PLO12
Self-control and responsibility
CO4: Develop positive attitudes and sports ethics during participation in Athletics activities	CLO7: Demonstrate a positive attitude and sportsmanship when participating in Athletics activities.	PLO15
CO5: Develop the ability to self-reflect, evaluate and suggest improvements during participation in Athletics activities	CLO8: Develop self-management and self-regulation skills to improve personal health and fitness through participation in Athletics activities.	PLO15
	CLO9: Reflect and evaluate personal progress in Athletics skills and understanding after completing the module, and propose measures for improvement.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Athletics Textbook/ Hanoi University of Physical Education and Sports, Sports Publishing House, 2014.

Reference

[2] Lecture notes compiled by the lecturer.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	– Diligent	Rubric 1	CLO7,8,9	10%
II	Course Test (up to 40%)
1	– Mid-term practical test	Rubric 2	CLO1,2,4,5,6	30%
III	Final exam (minimum 50%)
1	– Final practical test	Rubric 2	CLO3,6,7,8,9	60%

(Appendix 1 – Assessment Rubric attached)

MACL1052: Physical Education 2

General information about the course

Course name:				Course code: MACL1052
Vietnamese Name: Physical Education 2 English Name: Physical Education 2
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 01
Number of theoretical credits: 00	Number of practice credits: 01		Number of internship credits: 00
Number of theory periods: 00		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 15
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : Physical Education 1
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Ms. Nguyen Thi Hong Van	0978250950	van.nguyen@ttu.edu.vn	In charge

Brief description of course content

The course equips students with basic knowledge about the history and development of table tennis, basic technical principles in table tennis. The above knowledge helps students to be able to organize their own practice of table tennis techniques as well as practice general and specialized physical qualities.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic rules and regulations of Table Tennis.	CLO1: Understand the basic rules and regulations of Table Tennis.	PLO2
	CLO2: Master the basic methods and techniques of Table Tennis such as Ball feel, Movement techniques, Serving techniques, hitting the ball, etc.	PLO2
	CLO3: Master the theory of ball feel and movement techniques	PLO2
CO2: Understand the history and development of Table Tennis and its role in health and fitness.	CLO4: Present knowledge about the history and development of Table Tennis as well as understanding its impact on health and fitness.	PLO2
Skill
CO3: Develop basic skills in Table Tennis techniques and skills	CLO5: Perform basic Table Tennis techniques such as ball feel, movement, serving, hitting, etc.	PLO12
	CLO6: Perform forehand serve, backhand topspin serve, forehand smash	PLO12
Self-control and responsibility
CO4: Develop positive attitudes and sports ethics while participating in Table Tennis activities	CLO7: Demonstrate a positive attitude and sportsmanship when participating in Table Tennis activities	PLO15
CO5: Develop the ability to self-assess, evaluate and suggest improvements during participation in Table Tennis activities	CLO8: Develop self-management and self-regulation skills to improve personal health and fitness through participation in Table Tennis activities.	PLO14
	CLO9: Reflect and evaluate personal progress in Table Tennis skills and understanding after completing the course, and propose measures for improvement.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Athletics Textbook/ Hanoi University of Physical Education and Sports.- Hanoi: Sports Publishing House, 2014.

Reference

[2] Lecture notes compiled by the lecturer.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	Diligence	Rubric 1	CLO7,8,9	10%
II	Course Test (up to 40%)
1	Midterm practical test	Rubric 2	CLO1,2,4,5,6	30%
III	Final exam (minimum 50%)
1	Final practical test	Rubric 2	CLO3,6,7,8,9	60%

(Appendix 1 – Assessment Rubric attached)

MACL1053: Physical Education 3

General information about the course

Course name:				Course code: MACL1053
Vietnamese Name: Physical Education 3 English Name: Physical Education 3
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 01
Number of theoretical credits: 00	Number of practice credits: 01		Number of internship credits: 00
Number of theory periods: 00		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 15
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : Physical Education 2
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Ms. Nguyen Thi Hong Van	0978250950	van.nguyen@ttu.edu.vn	In charge

Brief description of course content

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic rules and regulations of Table Tennis.	CLO1: Understand the basic rules and regulations of Table Tennis.	PLO2
	CLO2: Master the basic methods and techniques of Table Tennis such as serving, hitting, pushing, etc.	PLO2
	CLO3: Master the theory of ball feel and movement techniques	PLO2
CO2: Understand the history and development of Table Tennis and its role in health and fitness.	CLO4: Present knowledge about the history and development of Table Tennis as well as understanding its impact on health and fitness.	PLO2
Skill
CO3: Develop basic skills in Table Tennis techniques and skills	CLO5: Perform basic Table Tennis techniques such as serving, hitting, pushing, etc.	PLO12
	CLO6: Perform backhand smash, forehand & backhand backspin serve, forehand & backhand push	PLO12
Self-control and responsibility
CO4: Develop positive attitudes and sports ethics while participating in Table Tennis activities	CLO7: Demonstrate a positive attitude and sportsmanship when participating in Table Tennis activities	PLO15
CO5: Develop the ability to self-assess, evaluate and suggest improvements during participation in Table Tennis activities	CLO8: Develop self-management and self-regulation skills to improve personal health and fitness through participation in Table Tennis activities.	PLO14
	CLO9: Reflect and evaluate personal progress in Table Tennis skills and understanding after completing the course, and propose measures for improvement.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

PLO1

PLO2

PLO3

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Athletics Textbook/ Hanoi University of Physical Education and Sports.- Hanoi: Sports Publishing House, 2014.

Reference

[1] Lecture notes compiled by the lecturer.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	Diligence	Rubric 1	CLO7,8,9	10%
II	Course Test (up to 40%)
1	Midterm practical test	Rubric 2	CLO1,2,4,5,6	30%
III	Final exam (minimum 50%)
1	Final practical test	Rubric 2	CLO3,6,7,8,9	60%

(Appendix 1 – Assessment Rubric attached)

ESL101: English 1

General information about the course

Course name:				Course code: ESL101
Vietnamese Name: English 1 English Name: English 1
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : None
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

This course aims to improve general English skills, meeting the requirements of learning and communicating in English. Lessons are oriented towards integrated skills (Listening, Speaking, Reading, Writing) and are delivered in real-life topics with pictures, stories, and video clips.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Huges, J. (2019). World English 1 (3rd ed.) . Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESLi101: Intensive English 1

General information about the course

Course name:				Course code: ESLi101
Vietnamese Name: Enhanced English 1 English Name: Intensive English 1
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : none
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Huges, J. (2019). World English 1 (3rd ed.). Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESL102: English 2

General information about the course

Course name:				Course code: ESL102
Vietnamese Name: English 2 English Name: English 2
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 1, Intensive English 1
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

This course continues the English 1 course, aiming to improve general English skills, meeting the requirements of studying and communicating in English. Lessons are oriented towards integrated skills (Listening, Speaking, Reading, Writing) and are delivered in real-life topics with pictures, stories, and video clips.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Huges, J. (2019). World English 1 (3rd ed.) . Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESLi102: Intensive English 2

General information about the course

Course name:				Course code: ESLi102
Vietnamese Name: English Intensive 2 English Name: Intensive English 2
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 1, Intensive English 1
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Huges, J. (2019). World English 1 (3rd ed.) . Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESL103: English 3

General information about the course

Course name:				Course code: ESL103
Vietnamese Name: English 3 English Name: English 3
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 2, Intensive English 2
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

This course is a continuation of General English 2 (ESL102), aiming to improve general English skills, meeting the requirements of learning and communicating in English. Lessons are oriented towards integrated skills (Listening, Speaking, Reading, Writing) and are delivered in real-life topics with pictures, stories, and video clips.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Chase, RT & Johannsen, KL (2019). World English 2 (3rd ed.). Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESLi103: Intensive English 3

General information about the course

Course name:				Course code: ESLi103
Vietnamese Name: English Intensive 3 English Name: Intensive English 3
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 0		Number of self-study hours: 60
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 2, Intensive English 2
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

Students are equipped with the knowledge and skills (Listening and Reading) necessary for the TOEIC test. After completing this course, students will achieve a score of 350-400 on the TOEIC test.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge on how to take the TOEIC test in two skills: Listening and Reading.	CLO1: Understand and remember the test formats and questions of TOEIC Listening and Reading skills.	PLO2
	CLO2: Systematize and generalize vocabulary and grammar knowledge of familiar topics in the TOEIC test.	PLO2
Skill
CO2: Improve the effectiveness of the TOEIC two-skill test.	CLO3: Develop listening skills to understand picture descriptions, questions and responses in common communication situations of the TOEIC Listening test.	PLO11
CO2: Improve the effectiveness of the TOEIC two-skill test.	CLO4: Identify and apply vocabulary and grammar to fill in the blanks in the TOEIC reading test.	PLO11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Lori. (2019). TNT TOEIC Basic (3rd ed.). Ho Chi Minh City General Publishing House.

Reference

[2]. Park, HY (2012). ABC TOEIC Reading Comprehension . Ho Chi Minh City General Publishing House.

[3]. Lee, SY (2012). ABC TOEIC Listening Comprehension . Ho Chi Minh City General Publishing House.

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESL104: English 4

General information about the course

Course name:				Course code: ESL104
Vietnamese Name: English 4 English Name: English 4
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 3, Intensive English 3
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

This course is a continuation of English 3 (ESL103), aiming to improve general English skills, meeting the requirements of studying and communicating in English. Lessons are oriented towards integrated skills (Listening, Speaking, Reading, Writing) and are delivered in real-life topics with pictures, stories, and video clips.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge of how to use English in everyday, academic and research contexts.	CLO1: Classify, compare, and apply grammatical structures for the purposes of daily communication, study, and research.	PLO2
	CLO2: Define and apply pre-intermediate to intermediate level vocabulary for daily communication, study and research purposes.	PLO2
Skill
CO2: Improve English listening, speaking, reading and writing skills.	CLO3: Analyze, synthesize, and debate scientific, cultural, and social topics.	PLO10, 11
	CLO4: Practice communicating and presenting in English on topics.	PLO10, 11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Chase, RT & Johannsen, KL (2019). World English 2 (3rd ed.). Heinle ELT.

Reference

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

ESLi104: Intensive English 4

General information about the course

Course name:				Course code: ESLi104
Vietnamese Name: English Intensive 4 English Name: Intensive English 4
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 02
Number of theoretical credits: 02	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 30		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 05
Number of other activities: 00
Prerequisites *(if any)* : English 3, Intensive English 3
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	MSc. Le Thi Diem Mi	0906909017	mi.le@ttu.edu.vn	In charge
2	Noah Moshe-lev Keogh	0935561283	noah.keogh@ttu.edu.vn	Join

Brief description of course content

Students are equipped with the knowledge and skills (Listening and Reading) necessary for the TOEIC test. After completing this course, students will achieve a score of 400-450 on the TOEIC test.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with knowledge on how to take the TOEIC test in two skills: Listening and Reading.	CLO1: Understand and remember the test formats and questions of TOEIC Listening and Reading skills.	PLO2
	CLO2: Systematize and generalize vocabulary and grammar knowledge of familiar topics in the TOEIC test.	PLO2
Skill
CO2: Improve the effectiveness of the TOEIC two-skill test.	CLO3: Develop listening skills to understand picture descriptions, questions and responses in common communication situations of the TOEIC Listening test.	PLO11
CO2: Improve the effectiveness of the TOEIC two-skill test.	CLO4: Identify and apply vocabulary and grammar to fill in the blanks in the TOEIC reading test.	PLO11
Self-control and responsibility
CO3: Be proactive in learning, manage time and collaborate effectively during learning and discussion.	CLO5: Ability to self-study, self-manage time and complete assignments effectively and on time.	PLO14
	CLO6: Demonstrate responsibility in lesson preparation, participate in classroom activities, and work effectively in groups to discuss and analyze problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

COURSE OUTPUT STANDARDS

OUTPUT STANDARDS OF THE TRAINING PROGRAM

Knowledge

Skill

Self-control and responsibility

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Lori. (2019). TNT TOEIC Basic (3rd ed.). Ho Chi Minh City General Publishing House.

Reference

[2] Park, HY (2012). ABC TOEIC Reading Comprehension . Ho Chi Minh City General Publishing House.

[3] Lee, SY (2012). ABC TOEIC Listening Comprehension . Ho Chi Minh City General Publishing House.

Assessment of learning outcomes

TT	Form and method of assessment		Assessment tools	Learning outcomes of the course	Weight
1	Process Assessment (A1)	Diligence (A1.1)	Rubrics (Appendix 1, Section 1)	CLO5,6	10%
1	Process Assessment (A1)	Quizzes (A1.2)	Multiple choice scale	CLO1,2,3,4	20%
2	Midterm Assessment: Multiple Choice and Essay (A3)		Rubrics Multiple Choice Scales and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4	20%
3	Final Assessment: Multiple Choice and Essay (A3)		Multiple choice scale and Rubrics (Appendix 1, Section 5)	CLO1,2,3,4,5,6	50%

(Appendix 1 – Assessment Rubric attached)

MATH101V: General Mathematics 1

General information about the course

Course name:				Course code: MATH101V
Vietnamese Name: General Mathematics 1 English Name: Calculus 1
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* : None
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

General Mathematics 1 course covers single-variable differential and integral calculus, with emphasis on applications in various contexts. It is the foundation for subsequent courses in mathematics, engineering and social sciences. The basic content covers Chapters 1 – 8 of James Stewart’s textbook. Major topics include: functions, limits of functions, continuity, derivatives, differentiation, applications of differentiation, integration, applications of integration in various fields (physics, engineering, economics and biology).

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master the concepts of functions, limits, differentiation and integration, and be able to find limits, derivatives and integrals of basic functions.	CLO1: Know and understand concepts related to functions, limits, differential and integral calculus of a variable.	PLO1
	CLO2: Calculate limits, derivatives and integrals of basic functions.	PLO6
CO2: Apply differential, integral and derivative calculus to solve real world problems.	CLO3: Use differential and integral calculus and derivatives to solve real-world problems.	PLO1,7a,7b
Skill
CO3: Equip teamwork skills and assign work	CLO4: Group work (discussion and presentation).	PLO10, 12
Level of autonomy and responsibility
CO4: Sense of responsibility	CLO5: Demonstrate responsibility and seriousness in studying.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] James Stewart, (2012), Calculus (Early Transcendentals) . Brooks/Cole Publishing Co.

Reference

[2] Robert T. Smith (2007). Calculus, Single Variable: Late Transcendental Functions . McGraw-Hill Higher Education.

[3] MyOpenMath: https://www.myopenmath.com/

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO4,5	10%
2	– Homework (individual).	Rubric AM2a	CLO1,2,3,5	10%
3	– Regular test (2 tests): Essay.	According to the answer	CLO1,2,3,5	10%
4	– Midterm test: Essay.	According to the answer	CLO1,2,3,5	30%
II	Final assessment (end of term)
1	– Essay test.	According to the answer	CLO1,2,3,5	40%

(Appendix – Assessment Rubric attached)

DSP101: Introduction to Data Science with Python

General information about the course

Course name:				Course code: DSP101
Vietnamese Name: Introduction to Data Science with Python English Name: Introduction to data science with Python
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

The course ” Introduction to Data Science with Python ” provides students with basic knowledge of data science, including the workflow of working with data, from collection, preprocessing, analysis to visualization. Students will learn how to use Python and popular libraries such as NumPy, Pandas, Matplotlib to process and analyze data, as well as implement basic machine learning models. The course concludes with a practical project, helping students apply the knowledge they have learned in practice.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide students with basic knowledge of Data Science and Python programming.	CLO1: Present basic concepts of Data Science and Python.	PLO1
	CLO2: Explain data processing and analysis methods.	PLO6
CO2: Develop data processing, analysis, and visualization capabilities using Python libraries such as Pandas, Matplotlib, and Seaborn.	CLO3: Apply Python libraries like Pandas, Matplotlib and Seaborn to process and visualize data.	PLO8
	CLO4: Analyze data using statistical methods.	PLO7a, 7b
	CLO5: Apply basic machine learning with Scikit-Learn to build and evaluate models.	PLO6
Skill
CO3: Develop self-study and time management skills.	CLO6: Develop self-study skills and effective time management.	PLO14
CO4: Teamwork and development of discussion and presentation skills.	CLO7: Practice teamwork through discussion and presentation activities.	PLO10,12
CO5: Develop skills in project implementation, report writing and presentation of results.	CLO8: Complete a data science project, write a report, and present the results.	PLO10
CO6: Work independently or in teams to complete data projects.	CLO9: Propose and carry out data science projects in practical or academic contexts.	PLO8
Level of autonomy and responsibility
CO7: Self-study and continue to improve programming and data analysis skills to adapt to new technologies.	CLO10: Self-research and apply new tools or algorithms to solve more complex problems in data science.	PLO13

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

CLO10

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Required (textbooks)

[1] Data Science from Scratch: First Principles with Python, 2nd Edition by Joel Grus. ISBN 9781492041139, O’reilly, 2019.

Reference

[1] Python Data Science Handbook: Essential Tools for Working with Data by Jake VanderPlas, ISBN 9781491912058, O’reilly, 2017.

[2] Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services, ISBN 9781118876138, John Wiley & Sons

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO6	5%
2	– Homework.	Rubric AM2a	CLO1,2,3,4,5,6,7,10	10%
3	– Regular test: Multiple choice.	According to the answer	CLO1-CLO6	10%
4	– Midterm exam: Essay.	According to the answer	CLO1-CLO6	30%
II	Final assessment (end of term)
1	– Do group projects.	Rubric AM8b	CLO1-CLO10	45%

(Appendix – Assessment Rubric attached)

EGD101: Engineering Design

General information about the course

Course name:				Course code: EGD101
Vietnamese Name: Technical Design English Name: Engineering Design
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: ☒ General overview of industry foundations Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Hoang Hai

0901 336 152

hhoang052@gmail.com

In charge

Brief description of course content

Engineering Design course equips students with the fundamental knowledge, processes, and tools needed to effectively implement engineering design projects. The content focuses on the main stages of the design process, from problem identification and analysis, idea generation to solution development, evaluation, and selection. Students will be guided in the use of important design tools such as modeling, value analysis, and project management techniques. In addition, the course also emphasizes the training of teamwork skills, professional communication, and raising the sense of professional responsibility, especially in the context of sustainable design and social responsibility. Through real-life projects, students will have the opportunity to apply theoretical knowledge to solve practical engineering problems, develop creative thinking and in-depth problem-solving skills.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master engineering design concepts and processes, from problem identification to solution development.	CLO1: Know and understand basic concepts and principles in engineering design.	PLO1
	CLO2: Understand the design process and tools that support it from problem identification to solution development.	PLO1
CO2: Apply theoretical knowledge to develop and evaluate effective design solutions.	CLO3: Apply theoretical knowledge to analyze and develop effective design solutions.	PLO1
	CLO4: Evaluate and make decisions on the feasibility and effectiveness of design options.	PLO1
Skill
CO3: Practice teamwork skills and present design solutions.	CLO5: Have effective teamwork skills in design projects.	PLO12
CO3: Practice teamwork skills and present design solutions.	CLO6: Have presentation, speaking and professional communication skills related to design solutions.	PLO10, 12
Level of autonomy and responsibility
CO4: Sense of responsibility.	CLO7: Demonstrate responsibility and seriousness in studying.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Dym, Clive L. (2013). Engineering design: a project-based introduction . Wiley.

Reference

[2] Arvid Eide, Roland Jenison, Larry Northup, Lane Masha w, (2002).. Introduction To Engineering Design and Problem Solving . McGraw-Hill Science Engineering .

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO7,5,6	5%
2	– Homework.	Rubric AM2a	CLO1,5,6	15%
3	– Midterm test: Essay.	According to the answer	CLO1,2,3,4	15%
4	– Simulation: Presentation and product demonstration (in groups).	Rubric AM8b	CLO1,2,3,4,5,6	30%
II	Final assessment (end of term)
1	Essay test.	According to the answer	CLO1,2,3,4	35%

(Appendix – Assessment Rubric attached)

MATH201V: General Mathematics 2

General information about the course

Course name:				Course code: MATH201V
Vietnamese Name: General Mathematics 2 English Name: Calculus 2
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview ☒ Industry foundation Industry foundation Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : General Mathematics 1 (MATH101V) or equivalent.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	090 805 1591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

Topics that will be covered in this second semester of introductory mathematics are improper integrals, introduction to probability and distributions, infinite series and sequences, Taylor polynomials, Fourier series, vectors and vector functions, partial differentiation, the Lagrange multiplier method, and topics in differential calculus.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Equip students with knowledge of infinite sums and improper integrals.	CLO1: Understand the concepts of infinite sums, improper integrals and their applications.	PLO6, 7a, 7b
CO2: Apply learned concepts to real-world problems and solve problems.	CLO2: Model and solve real-world problems using vector or multivariable functions.	PLO6, 7a, 7b
	CLO3: Use the Lagrange multiplier method to solve optimization problems.	PLO6, 7a, 7b
Skill
CO3: Develop the ability to self-improve knowledge for self-study; have teamwork, communication and reasoning skills.	CLO4: Have skills to search for documents and synthesize documents from different sources.	PLO9
	CLO5: Have the ability to reason and solve problems through basic math problems.	PLO10, 12
Level of autonomy and responsibility
CO4: Forming passion and interest in learning and research.	CLO6: Have a positive and cooperative attitude during the learning process; be dynamic and have career ambitions.	PLO14, 15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] James Stewart, (2012), Calculus (Early Transcendentals) . Brooks/Cole Publishing Co.

Reference

[2] Robert T. Smith (2007). Calculus, Single Variable: Late Transcendental Functions . McGraw-Hill Higher Education.

[3] MyOpenMath: https://www.myopenmath.com/

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO6	10%
2	– Homework (individual).	Rubric AM2a	CLO1, 2, 3, 4	10%
3	– Multiple choice test.	Multiple choice scale	CLO1, 2, 3, 5	15%
4	– Midterm test: Essay.	According to the answer	CLO1, 2, 3, 5	25%
II	Final assessment (end of term)
1	– Final exam: Essay.	According to the answer	CLO1, 2, 3, 5	50%

(Appendix – Assessment Rubric attached)

MATH110V: Linear Algebra

General information about the course

Course name:				Course code: MATH110V
Vietnamese Name: Linear Algebra English Name: Linear Algebra
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview ☒ Industry foundation Industry foundation Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

Linear Algebra course provides knowledge and applications of vectors, vector spaces, systems of linear equations, matrices, determinants, linear transformations, inner products, eigenvalues, eigenvectors, matrix diagonalization, etc.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Equip students with the most basic understanding of linear algebra.	CLO1: Know and understand knowledge and techniques of linear algebra.	PLO1, 6
CO2: Know how to apply learned knowledge to solve exercises.	CLO2: Solve linear algebra problems by hand and using computational software.	PLO1, 6
Skill
CO3: Problem solving skills.	CLO3: Solve practical problems in various fields using linear algebra.	PLO8
Level of autonomy and responsibility
CO4: Responsible for career, team, honesty; have team spirit and lifelong learning.	CLO4: Demonstrate honesty, seriousness and lifelong learning spirit in study and research.	PL013, 14, 15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] David C. Lay, Steven R. Lay, and Judi J. MacDonald, Pearson, (2016). Linear Algebra and Its Applications . Pearson.

Reference

[2] Gilbert Strang, (2005). Linear Algebra and Its Applications . Brooks/Cole INDIA.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO4	10%
2	– Homework (individual).	Rubric AM2a	CLO1, 2, 3, 4	10%
3	– Regular test (2 tests): Essay.	According to the answer	CLO1, 2, 3, 4	10%
4	– Test: Essay.	According to the answer	CLO1, 2, 3, 4	30%
II	Final assessment (end of term)
1	– Exam: Essay.	According to the answer	CLO1, 2, 3, 4	40%

(Appendix – Assessment Rubric attached)

PHYS101V: Introduction to Mechanics

General information about the course

Course name:				Course code: PHYS101V
Vietnamese Name: Introduction to Mechanics English Name: Introductory Mechanics
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview ☒ Industry foundation Industry foundation Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : None
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Hoang Hai	090 1336152	hhoang052@gmail.com	In charge

Brief description of course content

Mechanics is a branch of physics that studies the motion of objects. The aim of the Introduction to Mechanics course is to introduce undergraduate students (mainly first or second year students) to classical mechanics and its applications to practical problems in science and technology. Simulations, laboratory experiments and group work are also an important part of this course.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand and apply learned knowledge to solve mechanical problems in life	CLO1: Understand the basic concepts of classical mechanics.	PLO1
	CLO2: Understand the rules for measuring physical quantities.	PLO1
	CLO3: Apply the laws of motion to solve mechanical problems in life.	PLO1
	CLO4: Set up and perform experiments to verify physical phenomena.	PLO1
Skill
CO2: Equip yourself with the skills you need to work effectively	CLO5: Have comprehensive teamwork skills, including participating in discussions, giving opinions, listening, presenting and collaborating effectively to solve problems.	PLO10, 12
CO3: equipped with the ability to identify, analyze and find effective solutions to arising problems.	CLO6: Have the skills to identify problems, analyze causes, and provide optimal solutions confidently and independently.	PLO8
Level of autonomy and responsibility
CO4: Enhance autonomy and responsibility in learning	CLO7: Practice self-control in learning and be aware of responsibility to complete assigned tasks.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Raymond A. Serway and John W. Jewett, (2009). Physics for Scientists and Engineers with Modern Physics 8th edition . Brooks/Cole, Cengage Learning,

[2] Lab Manuals for Mechanics.

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO1, 2, 3, 4, 5, 6, 7	5%
2	Homework.	Rubric AM2a	CLO1, 2, 3, 4, 6, 7	15%
3	Midterm test: Essay.	According to the answer	CLO1, 2, 3, 4, 6	15%
4	Experiment/Simulation.	Rubric AM9	CLO1, 2, 3, 4, 5, 6, 7	30%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1, 2, 3, 4, 6	35%

(Appendix – Assessment Rubric attached)

PHYS110V: Introduction to Electricity and Magnetism

General information about the course

Course name:				Course code: PHYS110V
Vietnamese Name: Introduction to Electricity and Magnetism English name: Introductory Electricity and Magnetism
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview ☒Basic industry foundation Basic industry foundation Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisite *(if any)* : Introduction to Mechanics – PHYS101V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Hoang Hai	090 133 6152	hhoang052@gmail.com	In charge

Brief description of course content

Introduction to Electricity and Magnetism introduces the basic principles and concepts of electricity, magnetism, and optics, a branch of fundamental physics that continues the previous course in Mechanics. Topics covered include electric charges and electromagnetic fields, electric potential, electric circuits, magnetism, electromagnetic waves, and geometrical optics. In addition, this course will incorporate simulations, hands-on laboratory experiments, and collaborative group activities to enrich the learning experience.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand basic concepts, apply electromagnetic laws and use coding tools and software to solve problems in electricity, magnetism and optics.	CLO1: Understand the basic concepts of electricity, magnetism and optics.	PLO1
	CLO2: Apply the laws of electromagnetism to solve real-life physics challenges involving electricity, magnetism, and optics.	PLO1
	CLO3: Use coding tools and software to solve complex problems in the fields of electricity, magnetism and optics.	PLO1
CO2: Practice experimental skills and analyze physical phenomena.	CLO4: Set up and perform experiments to verify physical phenomena related to electricity, magnetism and optics.	PLO1
Skill
CO2: Equip yourself with the skills you need to work effectively.	CLO5: Students are equipped with comprehensive teamwork skills, including participating in discussions, giving opinions, listening, presenting and collaborating effectively to solve problems.	PLO10, 12
CO3: equipped with the ability to identify, analyze and find effective solutions to arising problems.	CLO6: Identify problems, analyze causes, and propose optimal solutions confidently and independently.	PLO8
Level of autonomy and responsibility
CO4: Enhance autonomy and responsibility in learning	CLO7: Practice self-control in learning and be aware of responsibility to complete assigned tasks.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Raymond A. Serway and John W. Jewett, Physics for Scientists and Engineers with Modern Physics 8th edition . Brooks/Cole, Cengage Learning,

[2] Lab Manuals.

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO1, 2, 3, 4, 5, 6, 7	5%
2	Homework.	Rubric AM2a	CLO1, 2, 3, 6, 7	15%
3	Experiment.	Rubric AM9	CLO1-CLO7	30%
4	Midterm test: Essay.	According to the answer	CLO1, 2, 3, 5, 6	15%
II	Final assessment (end of term)
1	Essay test.	According to the answer	CLO1-CLO7	35%

(Appendix – Assessment Rubric attached)

CS111V: Introduction to Computer Science and Python Programming

General information about the course

Course name:				Course code: CS111V
Vietnamese Name: Introduction to Computer Science and Python Programming English Name: Introduction to Computer Science and Programming in Python
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview ☒ Industry foundation Industry foundation Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits : 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* : None
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge

Brief description of course content

Introduction to Computer Science and Python Programming introduces the practices and principles of Computer Science and Programming and their impact and potential to change the world. Algorithms, problem solving, and programming techniques using a high-level language (Python) and design techniques that emphasize abstraction, encapsulation, problem decomposition, and recursion. Design, implement, and test programs. Topics also include object-oriented programming and popular Python libraries. Prerequisite for all other courses in Computer Science.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master basic knowledge of science and technology and its impact on society.	CLO1: Understand Computer Science and its principles and its impact on society.	PLO3-6
CO2: Identify algorithms and write large-scale Python programs.	CLO2: Identify algorithms to solve the problem.	PLO3-6
	CLO3: Develop and write a substantial program (500-1500 lines) in Python for a long-term project.	PLO3-6
CO4: Design, implement, test, debug Python programs.	CLO4: Design and implement programs using decomposition techniques (Top-Down design) and recursive techniques.	PLO3-6
	CLO5: Test and debug Python programs.	PLO3-6
	CLO6: Use Python IDE and libraries.	PLO3-6
Skill
CO5: Soft skills training.	CLO7: Group work (discussion and presentation).	PLO10, PLO12
CO5: Soft skills training.	CLO8: Search and read the information needed to solve the problem being encountered.	PLO9
Level of autonomy and responsibility
CO4: Enhance autonomy and responsibility in learning.	CLO9: Practice self-control in learning and be aware of responsibility to complete assigned tasks.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] John V. Guttag (2014). Introduction to Computation and Programming Using Python with Application to Understanding Data , 2nd Edition. Sean Morey.

[2] The Python Tutorial: https://docs.python.org/3/tutorial/

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Group exercise.	Rubric AM2b	CLO3-CLO9	40%
2	Individual exercise.	Rubric AM2a	CLO3,4,5,6
3	Midterm Exam: Multiple choice and essay.	According to the answer	CLO1-CLO9
II	Final assessment (end of term)
1	Paper test: Multiple choice and essay.	According to the answer	CLO1-CLO9	30%
2	Practice test.	Rubric AM9	CLO1-CLO9	30%

(Appendix – Assessment Rubric attached)

STA206V: Statistical Probability

General information about the course

Course name:				Course code: STA206V
Vietnamese Name: Statistical Probability English Name: Probabilities and Statistics
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 03		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* :
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	090 805 1591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

Probability and Statistics course deals with data analysis and statistical methods used primarily in business and economics. Major topics include: introduction to probability: distributions, expectations, variances, portfolios, central limit theorem; Statistical inference from univariate data: confidence intervals, hypothesis testing; Statistical inference from bivariate data: inference for simple linear regression models; and introduction to statistical computer packages.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master and apply learned knowledge to solve problems and requirements of the lesson.	CLO1: Calculate the probability of occurrences in a well-defined probability space.	PLO1, PLO7
	CLO2: Model the events of random phenomena using discrete/continuous random variables.	PLO1, PLO7
	CLO3: Know and understand sample statistics, such as sample mean and sample variance, from a data set.	PLO1, PLO7
	CLO4: Approximate the distribution of a sample using the central limit theorem.	PLO1, PLO7
	CLO5: Estimate unknown parameters using point/interval estimators.	PLO1, PLO7
	CLO6: Test the plausibility of statistical hypotheses based on information from the data set.	PLO1, PLO7
	CLO7: Perform linear regression analysis on a data set.	PLO1, PLO7
Skill
CO2: Apply teamwork and multimedia communication skills.	CLO8: Have teamwork skills, know how to use statistical computer libraries such as R/Python	PLO8, PLO12
Level of autonomy and responsibility
CO3: Responsible for career, self, honesty and lifelong learning.	CLO9: Demonstrate honesty, seriousness in studying, respect for people, yourself and your profession.	PLO13- PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1	4						4
CLO2	4						4
CLO3	4						4
CLO4	4						4
CLO5	4						4
CLO6	4						4
CLO7	4						4
CLO8								4				4
CLO9													3	3	3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Probability and Statistics for Engineering and the Sciences by Jay L. Devore, 9th edition, Brooks/Cole, Cengage Learning, 2016.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Attendance and test.	Rubric AM1	CLO1-CLO9	20%
2	– Homework (individual).	Rubric AM2a	CLO1-CLO8	20%
3	– Midterm test: Essay.	According to the answer	CLO1-CLO8	25%
II	Final assessment (end of term)
1	– Test: Essay.	According to the answer	CLO1-CLO8	35%

(Appendix – Assessment Rubric attached)

CS201V: Data Structures and Algorithms

General information about the course

Course name:				Course code: CS201V
Vietnamese Name: Data Structures and Algorithms English Name: Data Structure and Algorithms
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V (Introduction to Computer Science and Python Programming) or equivalent
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge

Brief description of course content

Analyze, use, and design data structures and algorithms using an object-oriented language such as Java to solve computational problems. Emphasis on abstraction including interfaces and abstract data types for arrays/lists, trees, sets, tables/maps, and graphs and their algorithms.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand basic data structures and their advantages and disadvantages.	CLO1: Understand and use basic data structures to store and retrieve ordered or unordered data, including: arrays, linked lists, binary trees, balanced trees, Heaps, hash tables, and graphs	PLO3-6
	CLO2: Implement algorithms to create, insert, delete, search, and sort each data structure.	PLO3-6
	CLO3: Recognize and apply appropriate data structures for software applications.	PLO3-6
Skill
CO2: Algorithm selection skills.	CLO4: Have the skills to select and propose appropriate algorithms for each specific problem.	PLO8
CO3: Improve search skills, self-study	CLO5: Skills to search and read information needed to solve the problem being encountered.	PLO9
Level of autonomy and responsibility
CO4: Forming a spirit of lifelong learning and the will to develop a career.	CLO6: Have the ability to self-study, self-research, accumulate knowledge and experience to improve professional qualifications, meet job requirements	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser, (2013). Data Structures and Algorithms in Python . Wiley.

Reference

[2] Karumanchi, Narasimha, (2017). Data Structures and Algorithms make easy: Data structures and Algorithmic Puzzles. CareerMonk.com

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Individual exercise.	Rubric AM2a	CLO1-6	30%
2	Midterm Exam: Essay.	According to the answer	CLO1-CLO6	30%
II	Final assessment (end of term)
1	Paper test: Essay.	According to the answer	CLO1-6	40%

(Appendix – Assessment Rubric attached)

CS202V: Discrete Mathematics for Computer Science

General information about the course

Course name:				Course code: CS202V
Vietnamese Name: Discrete Mathematics for Computer Science English Name: Discrete Mathematics for Computer Science
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Assoc. Prof. Dr. Tran Vu Khanh	0989 282 522	khanh.tran@ttu.edu.vn	In charge

Brief description of course content

Mathematics for Computer Science introduces the theory and practice of discrete mathematics – the science of discrete objects. Discrete mathematics is an important element in recognizing mathematical structures in objects and understanding their properties. This ability is especially important for computer scientists, software engineers, data scientists, security analysts, financial analysts, etc. Basic topics of Discrete Mathematics include Mathematical Logic, Sets, Relations, Number Theory, Induction and Recursion, Counting, Boolean Algebra, and Computational Modeling. It is a prerequisite for all other courses in Computer Science .

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master knowledge of Discrete Mathematics.	CLO1: Know and understand knowledge related to Discrete Mathematics (some concepts, terms, techniques, methods related to topics: mathematical logic, mathematical proof, sets, induction, recursion, number theory, counting, relations, Boolean algebra, computational models, etc.).	PLO1, 4-6
CO2: Apply learned knowledge in solving practical problems.	CLO2: Solve practical problems in various fields using Discrete Mathematics.	PLO1, 4-6
Skill
CO3: Proficient in the use of trained technical methods and proficient in at least one programming language.	CLO3: Select and propose solutions to solve some important applied problems and practical issues in the fields of economics and engineering.	PLO8
CO4: Have teamwork skills, planning, ability to assign, supervise and evaluate work completion.	CLO4: Teamwork, reporting, discussion and presentation skills.	PLO10, 12
Level of autonomy and responsibility
CO5: Forming a spirit of lifelong learning and the will to develop a career.	CLO5: Ability to self-study, self-research, accumulate knowledge and experience to improve professional qualifications, meet job requirements.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Kenneth H. Rosen (2012). Discrete Mathematics and Its Applications . McGraw-Hill.

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO4	10%
2	– Homework (individual).	Rubric AM2a	CLO4	10%
3	– Regular test: Essay.	According to the answer	CLO1-5	10%
4	– Midterm test: Essay.	According to the answer	CLO1-5	30%
II	Final assessment (end of term)
1	– Final exam: Essay.	According to the answer	CLO1-5	40%

(Appendix – Assessment Rubric attached)

CS203V: Organization of Computers

General information about the course

Course name:				Course code: CS203V
Vietnamese Name: Computer Organization English Name: Computer Organization
Courses: ☒Required Elective
Belonging to knowledge or skills: Industry Basics ☒Industry Basics Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V (Introduction to Computer Science and Python Programming)
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Hoang Anh	–	anh.hoang@ttu.edu.vn	In charge

Brief description of course content

Computer Organization course provides basic knowledge of hardware technology, C programming language, computer arithmetic, pipelines, memory hierarchy and input/output. In addition, the course helps students grasp the principles of computer operation, from understanding basic number systems and data representation to exploring how computers store and process information to perform calculations.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master and apply knowledge of programming and computer organization to practice and solve related problems.	CLO1: Understand computer organization and its impact on related fields.	PLO3-5
	CLO2: Develop and write an important program in C language.	PLO3-5
	CLO3: Design and implement Logic gates	PLO3-5
	CLO4: Test and debug assembly programs.	PLO3-5
Skill
CO2: Develop teamwork skills, while improving the ability to work independently and search for information.	CLO5: Teamwork, discussion, reporting and presentation skills.	PLO10, 12
	CLO6: Independent working skills: search and read information needed to solve exercises and assignments.	PLO9
Level of autonomy and responsibility
CO3: Demonstrate a sense of professional responsibility and lifelong learning.	CLO7: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] David A. Patterson, John L. Hennessy, (2013). Computer Organization and Design, The Hardware/Software Interface . Fifth Edition. Morgan Kaufmann.

[2] The C Programming Tutorial: https://www.w3resource.com/index.php

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO7	10%
2	Homework (individual).	Rubric AM2a	CLO1, 2, 3, 4, 6, 7	10%
3	Midterm Test: Report.	Rubric AM7	CLO1, 2, 3, 4, 6	30%
II	Final assessment (end of term)
1	Group project.	Rubric AM8b	CLO1-CLO7	50%

(Appendix – Assessment Rubric attached)

CS204V: Algorithm Design and Analysis

General information about the course

Course name:				Course code: CS204V
Vietnamese Name: Algorithm Design and Analysis English Name: Design and Analysis of Algorithms
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS201V (Data Structures and Algorithms)
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Anh Tuan	–	tuan.tran@ttu.edu.vn	In charge

Brief description of course content

Design and Analysis of Algorithms course is the study of algorithm design, algorithm complexity analysis, and problem complexity analysis. Design techniques include brute force, reduce, divide and conquer, dynamic programming, greedy algorithms, iterative improvement, backtracking, and branching and binding. The course is organized around some of the basic strategies of algorithm design, and algorithm design will be taught on par with analysis. Some more abstract but important topics will also be covered: NP-completeness, approximation algorithms, and lower bounds.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand algorithmic concepts and process mechanisms	CLO1: Understand algorithm design and solve problems using basic techniques.	PLO3-6
CO1: Understand algorithmic concepts and process mechanisms	CLO2: Understand the complexity analysis of algorithms.	PLO3-6
CO2: Master the knowledge learned and apply algorithm design and complexity	CLO3: Understand the relationship between problem solving, algorithm design, and complexity analysis.	PLO3-6
	CLO4: Apply algorithm design, analysis and implementation in various applications. Use Python to measure algorithm complexity.	PLO3-6
Skill
CO3: Apply, evaluate and analyze algorithms in problem-solving applications	CLO5: Develop creativity and strategies to solve problems.	PLO8
	CLO6: Have teamwork skills (discussion and presentation).	PLO10, 12
	CLO7: Have the skills to search and read the information needed to solve problems.	PLO9
Level of autonomy and responsibility
CO4: Forming passion and interest in learning and research.	CLO8: Have a positive and cooperative attitude during the learning process; be dynamic and have career ambitions.	PLO14, 15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Anany Levitin (2011). Introduction to The Design and Analysis of Algorithms (3rd ed) . Addison Wesley.

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Assessment
1	Individual exercise.	Rubric AM2a	CLO 1,2,3,7,8	30%
2	Midterm Exam: Essay.	According to the answer	CLO1-CLO8	30%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1-CLO8	40%

(Appendix – Assessment Rubric attached)

CS205V: Operating System

General information about the course

Course name:				Course code: CS205V
Vietnamese Name: Operating System English Name: Introduction to Operating Systems
Courses: ☒Required Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V (Introduction to Computer Science) or equivalent
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Anh Tuan	–	tuan.tran@ttu.edu.vn	In charge

Brief description of course content

Operating Systems course provides introductory concepts that serve as the foundation of an operating system—a key part of any computer system. In particular, the course covers topics such as process and thread management, CPU scheduling, process synchronization and deadlock handling, memory management, I/O devices and storage management, file systems, security, and protection mechanisms.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master the basic concepts of operating systems, including definition, functions, and application on popular platforms such as Windows, Unix, Mac OS, and mobile operating systems.	CLO1: Know and understand basic but important concepts of operating systems, including their definition, functions, and how to design and build them.	PLO3-6
	CLO2: Understand the basic concepts of operating systems implemented on popular operating systems such as MS Windows, Unix, Mac OS and others (both traditional operating systems for personal computers and servers as well as operating systems for mobile devices).	PLO3-6
Skill
CO2: Carry out projects to research modern operating systems and apply concepts learned in class to practice.	CLO3: Carry out projects to explore modern operating systems and relate them to concepts learned in class.	PLO8-9
Level of autonomy and responsibility
CO3: Forming passion and interest in learning and research.	CLO4: Have a positive and cooperative attitude during the learning process; be dynamic and have career ambitions.	PLO14, 15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] A. Silberschatz, PB Galvin, and G. Gagne (2018). Operating System Concepts (10th Ed) . John Wiley & Sons.

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO4	5%
2	Group report.	Rubric AM8b	CLO1, 2, 3	5%
3	Individual exercises (homework).	Rubric AM2a	CLO1, 2, 3	5%
4	Regular Tests 1 and 2: Multiple Choice and Essay.	According to the answer	CLO1, 2, 3	10%
5	Midterm Exam: Multiple choice and essay.	According to the answer	CLO1, 2, 3	30%
II	Final assessment (end of term)
1	Final exam: Multiple choice and essay.	According to the answer	CLO1-CLO4	45%

(Appendix – Assessment Rubric attached)

CS206V: Object Oriented Programming

General information about the course

Course name:				Course code: CS206V
Vietnamese Name: Object Oriented Programming English Name: Object Oriented Programming
Courses: ☒Required Elective
Belonging to knowledge or skills: Overview of industry foundations ☒ Industry foundations Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V (Introduction to Computer Science and Python Programming)
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge

Brief description of course content

Object Oriented Programming course introduces the object-oriented approach to programming using the Java language. The goal is to help students gain an understanding of the basic concepts of object-oriented programming such as objects, classes, methods, inheritance, polymorphism, and interfaces, along with the basic principles of abstraction, modularity, and reuse in object-oriented design.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the concept of Object Oriented Programming (OOP) and its importance in software development.	CLO1: Know and understand Object Oriented Programming (OOP) and why it is important in software development.	PLO3-6,7c
CO2: Apply OOP to design, develop, test and debug large scale software projects in Java, using Java IDE and libraries.	CLO2: Apply OOP in software design and development.	PLO3-6,7c
	CLO3: Develop and write a substantial program (2000-5000 lines) in Java for a software project.	PLO3-6,7c
	CLO4: Test and debug Java programs.	PLO3-6,7c
	CLO5: Can use Java IDE and libraries.	PLO3-6,7c
Skill
CO3: Develop practical programming skills.	CLO6: Have practical programming skills.	PLO8
CO4: Have the ability to look up information and research to solve problems.	CLO7: Skills to search and read information needed to solve the problem being encountered.	PLO9
Level of autonomy and responsibility
CO5: Demonstrate a sense of professional responsibility and lifelong learning.	CLO8: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7			PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	a	b	c	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			5	5	5	5			5
CLO2			5	5	5	5			5
CLO3			5	5	5	5			5
CLO4			5	5	5	5			5
CLO5			5	5	5	5			5
CLO6										4
CLO7											3
CLO8															4	4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Building Java Programs: A Back to Basics Approach , 2nd edition by Stuart Reges and Marty Stepp

[2] The Java Tutorials. http://download.oracle.com/javase/tutorial/index.html

Reference

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Assessment
1	Attendance and activity in class.	Rubric AM1	CLO8	40%
2	Group exercise.	Rubric AM2b	CLO2, 3, 4, 7
3	Individual exercise.	Rubric AM2a	CLO2, 3, 4, 7
4	Midterm Exam: Essay.	According to the answer	CLO2, 3, 4, 7
II	Final assessment (end of term)
1	Paper test: Essay.	According to the answer	CLO1-CLO8	30%
2	Practice test.	Rubric AM9	CLO1-CLO8	30%

(Appendix – Assessment Rubric attached)

CS301V: Software Design and Implementation

General information about the course

Course name:				Course code: CS301V
Vietnamese Name: Software design and implementation English Name: Software Design and Implementation
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS201V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge

Brief description of course content

Techniques for designing and building reliable, maintainable, and useful software systems. Programming models and tools for medium to large scale projects: version control, support tools, performance analysis, UML, design patterns, software architecture, GUI and usability, software engineering, testing, and documentation.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Knowledge to translate vague descriptions and aspirations into a system design that is buildable, maintainable, and extensible. Prioritize features that need to be built first, then refine and extend the project through multiple experimental releases.	CLO1: Design a software application using existing design patterns. Write efficient, proficient code.	PLO3-6,7c
	CLO2: Presentation is designed in UML language. Tools used: IntelliJ IDEA, Maven, Git, UML, Docker.	PLO3-6,7c
	CLO3: Design a user interface (GUI) using Swing library and evaluate its usability	PLO3-6,7c
Skill
CO2: Essential tools for software project development as well as skills: report writing, teamwork, test case definition.	CLO4: Draft documents and reports.	PLO12
	CLO5: Teamwork and presentation skills.	PLO10
reliance and responsibility
CO3: Ability to self-research, learn and apply new technologies in the field of big data.	CLO6: Actively learn and update new technologies in the field of big data.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

There are no required readings, but students are encouraged to read the following:

[1] Effective Java, 2nd Ed , Joshua Bloch, ISBN: 978-0-321-35668-0

[2] UML Tutorial , http://www.uml.org/ or http://www.smartdraw.com/resources/tutorials/uml-diagrams/

[3] Design Patterns in Java Tutorial (tutorialspoint.com)

[4] Java Concurrency In Practic e, Brian Goetz et al, ISBN: 978-0-321-34960-6

[5] Design principles : http://www.oodesign.com/design-principles.html

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Report.	Rubric AM7	CLO1,2,5	30%
2	Code.	Rubric AM9	CLO4, 6	20%
3	Demo + Presentation.	Rubric AM8b	CLO1-6	20%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1-6	30%

(Appendix – Assessment Rubric attached)

CS302V: Web Application Development

General information about the course

Course name:				Course code: CS302V
Vietnamese Name: Web Application Development English Name: Web Application Development
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS301V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

0983 695 166

dung.cao@ttu.edu.vn

In charge

Brief description of course content

Web Application Development course provides basic and advanced knowledge for students to build, deploy, and maintain modern web applications, from frontend using HTML, CSS, JavaScript to backend processing with Node.js, Express, and database integration such as MongoDB. This is a core course in the information technology program, helping students become familiar with popular tools such as React, master the process of deploying and securing web applications, and closely connect with courses such as Programming Fundamentals and Databases, providing good support for studying Advanced Software Development or System Administration.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master basic knowledge of frontend.	CLO1: Understand and master basic frontend technologies such as HTML, CSS, and JavaScript/React to develop user interfaces for web applications.	PLO3-6, 7c
CO2: Learn backend development with Node.js, Express, MongoDB.	CLO2: Master the principles and techniques of backend development using Node.js, Express, combined with MongoDB database, building RESTful APIs and handling HTTP requests.	PLO3-6, 7c
CO3: Master knowledge of Web security.	CLO3: Master the process of deploying web applications to production environments and implementing basic security measures such as data encryption, SQL Injection, XSS, and CSRF prevention.	PLO3-6, 7c
Skill
CO4: Select, propose solutions to build and deploy complete web applications.	CLO4: Select and propose solutions to build fully functional web applications from frontend to backend, integrate with database and deploy in real environment.	PLO8
CO5: Effective teamwork skills in application development and project management.	CLO5: Have effective teamwork skills in application development and project management.	PLO 10, 12
reliance and responsibility
CO6: Improve the ability to evaluate and improve web applications based on real-world feedback.	CLO6: Responsible for application quality and continuous improvement.	PLO13, 15
	CLO7: Be proactive in searching and learning new technologies and tools in the field of web application development.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Elizabeth Naramore et al. (2008). Beginning PHP5, Apache, Mysql Web Development . Wiley India Pvt.Ltd.

Reference

[1] Singh, Anubha, (2020). Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow . Packt Publishing.

[2] David Choi, (2020). Full-Stack React, TypeScript, and Node: Build cloud-ready web applications using React 17 with Hooks and GraphQL . Packt Publishing.

[3] Other sources of information on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO7	10%
2	– Practice.	Rubric AM9	CLO1- CLO6	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO7	20%
II	Final assessment (end of term)
1	– Do group projects (code, write reports, present and demo).	Rubric AM8b	CLO1- CLO7	50%

(Appendix – Assessment Rubric attached)

CS303V: Mobile Application Development

General information about the course

Course name:				Course code: CS303V
Vietnamese Name: Mobile Application Development English Name: Mobile Application Development
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS301V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge

Brief description of course content

Mobile Application Development is a specialized course that helps students master the knowledge and skills of developing applications on mobile platforms (Android and iOS). The course provides knowledge about application architecture, user interface (UI/UX), data processing, API integration, and application deployment to Google Play or App Store. This is a foundational course that connects with courses such as Basic Programming, Database, and prepares for advanced courses.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Know and understand the basic principles of mobile application development.	CLO1: Know and understand the basic concepts in mobile application development (Android and iOS).	PLO3-7
	CLO2: Understand the principles of user interface design (UI/UX) and how to handle data in mobile applications.	PLO3-7
	CLO3: Understand APIs, communication methods between application components and external systems.	PLO3-7
Skill
CO2: Develop practical mobile application programming skills. Apply programming knowledge to real-world application development.	CLO4: Develop basic mobile applications with features such as data management, event handling, and user interaction. Integrate external APIs and services into mobile applications.	PLO8
	CLO5: Design user interface compatible with multiple screen sizes and mobile platforms.	PLO8
	CLO6: Perform mobile application testing techniques to ensure performance and stability. Submit applications to app stores such as Google Play and App Store.	PLO8
CO3: Effective teamwork skills in application development and project management.	CLO7: Have effective teamwork skills in application development and project management.	PLO10, 12
Self-control and responsibility
CO4: Develop creative thinking and problem solving.	CLO8: Have a sense of responsibility and professional ethics in application development, especially regarding user security and privacy.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

WORRY

PLO12

WORRY

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Harrel, William.. (2011). HTML, CSS & JavaScript mobile development for dummies . Wiley.

Reference

[1] Brian Fling, (2009). Mobile Design and Development: Practical concepts and techniques for creating mobile sites and web apps, 1st edition . O’Reilly Media.

[2] Lee, Wei-Meng , (2012). Beginning Android 4 Application Development . John Wiley & Sons, Inc

[3] Harris, Nick. (2014). Beginning iOS Programming: Building and Deploying iOS Applications. Wrox

[4] James, Derek, (2013). Android game programming for dummies . John Wiley

[5] Daley, Michael, (2011) . Learning iOS game programming Addison-Wesley.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO8	10%
2	– Practice.	Rubric AM9	CLO1- CLO6	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO8	20%
II	Final assessment (end of term)
1	– Do group projects (code, write reports, present and demo).	Rubric AM8b	CLO1- CLO8	50%

(Appendix – Assessment Rubric attached)

CS304V: IoT Application Development

General information about the course

Course name:				Course code: CS304V
Vietnamese Name: IoT Application Development English Name: IoT Application Development
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 45
Number of other activities: 00
Prerequisite *(if any)* : CS301V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

IoT Application Development is an elective course that provides students with the knowledge and skills needed to design and deploy IoT applications in areas such as smart homes, smart agriculture, and Industry 4.0. This course equips students with an understanding of IoT system architecture, microcontroller programming (Arduino, ESP32), communication protocols (MQTT, HTTP), sensor and actuator integration, and cloud-based data analysis. This is a foundational course for students to apply knowledge from Computer Networks, Embedded Programming, etc.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide comprehensive knowledge of Internet of Things (IoT) systems and applications	CLO1: Understand, analyze and present IoT system architecture as well as operating principles of IoT components.	PLO3-7
	CLO2: Describe IoT communication protocols (MQTT, HTTP) accurately.	PLO3-7
	CLO3: Analyze the process of integrating sensors and actuators.	PLO3-7
	CLO4: Master the principles of IoT data processing and analysis.	PLO3-7
Skill
CO2: Develop in-depth practical skills in designing, programming and implementing IoT solutions	CLO5: Design and develop IoT applications from basic to advanced, including: configuring and integrating IoT components and building IoT systems to connect and transmit data. Deploying IoT solutions on cloud platforms.	PLO8
CO3: Soft skills (criticism, presentation, teamwork, etc.)	CLO6: Have teamwork skills, report presentation, effective communication, clear and convincing.	PLO10, 12
Self-control and responsibility
CO: Improving the capacity to apply IoT technology in practical fields such as smart homes, agriculture and industry	CLO7: Be aware of researching and updating IoT technology trends.	PLO14
	CLO8: Develop professionalism and professional ethics.	PLO13

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Arshdeep Bahga, Vijay Madisetti, (2014). Internet of Things: A Hands-on Approach . Universities Press.

Reference

[1] Maciej Kranz, (2016). Building the Internet of Things: Implementing New Business Models, Disrupt Competitors, Transforming Your Industry , 1st Edition . Wiley.

[2] Le My Ha, Pham Quang Huy, (2017). IoT programming with Arduino , Thanh Nien Publishing House.

[3] Online documents.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1.	CLO8	10%
2	– Practice.	Rubric AM9	CLO3, 4	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO7	20%
II	Final assessment (end of term)
1	– Do projects (write reports and presentations, code, demo code).	Rubric AM8b	CLO1- CLO7	50%

(Appendix – Assessment Rubric attached)

CS305V: Cloud Computing

General information about the course

Course name:				Course code: CS305V
Vietnamese Name: Cloud Computing English Name: Cloud Computing
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS440V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Truong Huu Tram

–

tram.truong-huu@ttu.edu.vn

In charge

Brief description of course content

Cloud Computing course plays an important role in equipping students with fundamental knowledge and practical skills in cloud technology, a rapidly growing field with wide applications in the information technology industry. Students will learn about basic concepts, service models (IaaS, PaaS, SaaS), advanced technologies such as Containers, Serverless, and DevOps on the cloud. At the same time, the course provides skills in deployment, management, resource optimization, and security on popular cloud platforms such as AWS, Azure, and Google Cloud.

The course has a close relationship with other subjects in the program such as Operating Systems, Computer Networks, Databases, and Software Development, creating a premise for students to apply cloud technology to different fields in the information technology industry.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide comprehensive theoretical and practical knowledge of cloud computing.	CLO1: Understand and analyze basic concepts of cloud computing. Present service models (IaaS, PaaS, SaaS).	PLO4-7
	CLO2: Distinguish between advanced technologies such as containers, serverless, DevOps. Implement application deployment on cloud platforms (AWS, Azure, Google Cloud).	PLO4-7
Skill
CO2: Develop in-depth skills in designing, implementing and administering cloud computing systems.	CLO3: Configure and manage cloud computing infrastructure. Design, select, and recommend effective and secure cloud solutions.	PLO8
CO3: Teamwork and presentation skills.	CLO4: Willing to share and work in groups.	PLO12
Self-control and responsibility
CO4: Improve the capacity to apply cloud technology to solve practical problems in the field of information technology.	CLO5: Have the awareness to self-study, self-research and update new technology trends.	PLO14
	CLO6: Develop professionalism and professional ethics.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Hwang, Kai, Jack Dongarra, and Geoffrey C. Fox. (2013). Distributed and cloud computing: from parallel processing to the internet of things . Springer.

Reference

[1] Rountree, Derrick, and Ileana Castrillo. (2013). The Basics of Cloud Computing: Understanding the Fundamentals of Cloud Computing in Theory and Practice . Newnes

[2] To Thanh Hai (2011). Exploiting some Cloud Computing services . Phuong Dong Publishing House.

[3] Thomas Erl, Ricardo Puttini, Zaigham Mahmood (2013). Cloud Computing: Concepts, Technology & Architecture, 1st Edition . Pearson.

[4] AWS website: https://aws.amazon.com/

Microsoft Azure website : https://azure.microsoft.com/

Google Cloud website : https://cloud.google.com/

[7] Online courses:

AWS Training and Certification.
Google Cloud Training.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO5, 6	10%
2	– Practice.	Rubric AM9	CLO3, 4	20%
3	– Midterm test: Presentation.	Rubric AM8b	CLO1-CLO4	30%
II	Final assessment (end of term)
1	– Do group projects (write reports and give presentations).	Rubric AM8b	CLO1-CLO6	40%

(Appendix – Assessment Rubric attached)

CS311V: Introduction to Databases

General information about the course

Course name:				Course code: CS311V
Vietnamese Name: Introduction to Database English Name: Introduction to Database
Courses: ☒Required Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS201V (Data Structures and Algorithms) and Introduction to JavaScript and/or Python
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.email	In charge

Brief description of course content

Introduction to Databases course provides students with a solid foundation in database systems. Topics include: data modeling, database design theory, data definition and manipulation languages (e.g., SQL), indexing techniques, query processing and optimization, and database programming interfaces. In addition to relational and semi-structured databases (e.g., JSON), the course also introduces a number of other topics related to data management, distributed storage, and parallel processing.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master the basic concepts of data modeling and database systems	CLO1: Analyze and design a database for a software application.	PLO3-7
	CLO2: Understand the basics of Database Management Systems (DBMS).	PLO3-7
CO2: Understand and use Database Management Systems (DBMS) and modern storage systems.	CLO3: Use SQL language to create, query and edit databases.	PLO3-7
	CLO4: Understand semi-structured formats like JSON and use them in applications through libraries/APIs.	PLO3-7
	CLO5: Can use database management systems such as: MySQL, MongoDB.	PLO3-7
CO3: Apply knowledge to real-world case studies.	CLO6: Develop a software application using a database system.	PLO3-7
Skill
CO4: Develop teamwork skills (discussion, presentation), report writing, and searching for information needed to solve problems.	CLO7: Group work (discussion and presentation)	PLO12
	CLO8: Writing a report	PLO10
	CLO9: Search and read information needed to solve a problem	PLO9
Level of autonomy and responsibility
CO5: Demonstrate a sense of professional responsibility and lifelong learning.	CLO10: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7			PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	a	b	c	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4	4	4
CLO2			4	4	4	4	4	4	4
CLO3			4	4	4	4	4	4	4
CLO4			4	4	4	4	4	4	4
CLO5			4	4	4	4	4	4	4
CLO6			4	4	4	4	4	4	4
CLO7														4
CLO8												4
CLO9											3
CLO10															3	3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Hector Garcia-Molina, Jeffrey D. Ullman and Jenifer Widom; Database Systems: The Complete Book , 2nd Ed (2008), ISBN-13: 978-0-13-187325-4. (TTU’s Library)

[2] Online tutorial of MySQL, MongoDB, React

Assessment of learning outcomes

TT	Form and method of assessment	Tools Evaluate	Learning outcomes of the course	Weight
I	Progress Evaluation:			50%
1	Group Project: Database Design.	Rubric AM8b	CLO1-CLO10	15%
2	Team Project: Source Code (GUI, API).	Rubric AM8b		20%
3	Group Project: Report and Presentation.	Rubric AM8b		15%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1-CLO10	50%

(Appendix – Assessment Rubric attached)

CS330V: Introduction to Artificial Intelligence

General information about the course

Course name:				Course code: CS330V
Vietnamese Name: Introduction to Artificial Intelligence English Name: Introduction to AI
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* : CS111V, CS202V or MATH110V or STA206V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Ta The Anh	–	anh.ta@ttu.edu.vn	In charge

Brief description of course content

Introduction to Artificial Intelligence introduces the fundamental concepts of Artificial Intelligence (AI). The course focuses on the fundamental aspects of AI as the study of agents that are capable of perception and action. Students will learn about classical problem-solving strategies such as search and planning, as well as more modern topics such as knowledge representation and machine learning. Programming exercises will be assigned to illustrate the theoretical material. Upon completion of this course, students will have a solid foundation in the fundamental topics of Artificial Intelligence.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provides an overview of artificial intelligence including: basic AI concepts, principles and developing modeling and analytical skills to apply AI to problem solving	CLO1: Know and understand the basic principles and assumptions behind artificial intelligence	PLO3-6, 7b
	CLO2: Select and apply different artificial intelligence algorithms	PLO3-6, 7b
Skill
CO4: Search for information and work effectively in groups.	CLO3: Group work (discussion and presentation)	PLO10, PLO12
CO4: Search for information and work effectively in groups.	CLO4: Search and read information needed to solve a problem	PLO8
reliance and responsibility
CO5: Ability to self-research, learn and apply new technologies in the field of AI.	CLO5: Actively learn and update new technologies in the field of big data.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Stuart J. Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd Ed . Pearson.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Programming exercises (individual).	Rubric AM2a	CLO2, 4	30%
2	Programming exercises (group).	Rubric AM2b	CLO3, 5	30%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1, 2	40%

(Appendix – Assessment Rubric attached)

CS331V: Introduction to Data Mining

General information about the course

Course name:				Course code: CS331V
Vietnamese Name: Introduction to Data Mining English Name: Introduction to Data Mining
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS201V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Hoang Anh	–	anh.hoang@ttu.edu.vn	In charge

Brief description of course content

Data mining is the process of finding descriptive, understandable, and predictive models from large data sets. The main parts of this course include data mining analysis, frequent pattern and association rule mining, clustering, and classification. The course provides these fundamentals, while also covering advanced topics such as kernel methods, multidimensional data analysis, and complex graphs and networks. The course integrates concepts from related disciplines such as machine learning and statistics, and is suitable for a course in data analysis.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master knowledge of data mining, including methods for each type of data	CLO1: Know how to analyze data for discovery.	PLO3-6,7a,7b
	CLO2: Know how to exploit frequently occurring patterns.	PLO3-6,7a,7b
	CLO3: Understand how classification is achieved in supervised learning.	PLO3-6,7a,7b
	CLO4: Implement data clustering techniques in unsupervised learning.	PLO3-6,7a,7b
	CLO5: Know and understand how to detect outlier data.	PLO3-6,7a,7b
Skill
CO2: Teamwork and information seeking skills	CLO6: Have teamwork skills (discussion and presentation)	PLO10, 12
CO2: Teamwork and information seeking skills	CLO7: Find and read information needed to solve a problem	PLO9
Level of autonomy and responsibility
CO3: Demonstrate a sense of professional responsibility and lifelong learning.	CLO8: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7			PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	a	b	c	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	5	5
CLO2			4	4	4	4	5	5
CLO3			4	4	4	4	5	5
CLO4			4	4	4	4	5	5
CLO5			4	4	4	4	5	5
CLO6												4		4
CLO7											4
CLO8															4	4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Mohammed J. Zaki Wagner Meira Jr, (2014). Data Mining and Machine Learnings: Fundamental Concepts and Algorithms . Cambridge University Press.

Reference

[1] Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman (2014). Mining of Massive Datasets . Cambridge University Press.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Individual exercise.	Rubric AM2a	CLO2-CLO5	30%
2	Midterm Exam: Test (multiple choice and essay).	According to the answer	CLO1-CLO5	30%
II	Final assessment (end of term)
1	Final group project.	Rubric AM8b	CLO1-CLO8	40%

(Appendix – Assessment Rubric attached)

CS332V: Introduction to Machine Learning

General information about the course

Course name:				Course code: CS332V
Vietnamese Name: Introduction to Machine Learning English Name: Introduction to Machine Learning
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS201V, MATH201V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.email	In charge

Brief description of course content

The Introduction to Machine Learning course will provide an overview of the fundamentals of machine learning. Students will learn about the types of problems that can be solved, the basic components, and how to build models in machine learning. Several key algorithms will be explored. Upon completion of the course, students will have a working knowledge of several supervised and unsupervised learning algorithms, along with an understanding of important concepts such as underfitting and overfitting, regularization, and cross-validation. Students will be able to identify the type of problem they are trying to solve, select appropriate algorithms, tune parameters, and evaluate models.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide basic concepts of Machine Learning	CLO1: Know and understand machine learning concepts and algorithms.	PLO3-6, 7a,7b
CO1: Provide basic concepts of Machine Learning	CLO2: Selecting the appropriate machine learning algorithm to solve real-world problems.	PLO3-6, 7a,7b
CO2: Provide practical knowledge of some supervised and unsupervised learning algorithms.	CLO3: Develop and write important machine learning models/functions in Python.	PLO3-6, 7a,7b
	CLO4: Use Scikit Learn to solve machine learning problems.	PLO3-6, 7a,7b
	CLO5: Test and evaluate machine learning models.	PLO3-6, 7a,7b
Skill
CO3: Ability to identify the type of machine learning problem in practice, choose appropriate algorithms, models, and fine-tune parameters to solve the problem.	CLO6: Group work (discussion, reporting and presentation)	PLO10, 12
	CLO7: Search and read information needed to solve a problem	PLO8
Level of autonomy and responsibility
CO4: Demonstrate a sense of professional responsibility and lifelong learning.	CLO8: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7			PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	a	b	c	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	5	5
CLO2			4	4	4	4	5	5
CLO3			4	4	4	4	5	5
CLO4			4	4	4	4	5	5
CLO5			4	4	4	4	5	5
CLO6												4		4
CLO7										4
CLO8															3	3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Vu Huu Tiep, Basic Machine Learning , https://machinelearningcoban.com/ (TTU Library).

[2] Scikit: learn: https://scikit-learn.org/stable/

Reference

[1] Mitchell, Tom (1997). Machine Learning . McGraw-Hill.

[2] Machine Learning courses: MIT, Bekerly, Coursera, Edx.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Individual exercise.	Rubric AM2a	CLO3-CLO5	20%
2	Group exercise.	Rubric AM2b	CLO1-CLO8	40%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1-CLO8	40%

(Appendix – Assessment Rubric attached)

CS333V: Introduction to Computer Vision

General information about the course

Course name:				Course code: CS333V
Vietnamese Name: Introduction to Computer Vision English Name: Introduction to Computer Vision
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS111V, MATH110V (Consult Academic Advisor)
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Tran Anh Tuan

–

tuan.tran@ttu.edu.vn

In charge

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

Join

Brief description of course content

The course ” Introduction to Computer Vision ” introduces basic concepts and techniques in the field of Computer Vision, an important branch of Artificial Intelligence. The course equips students with knowledge of image processing, image analysis, feature extraction and object recognition in images and videos. This course is the foundation for more in-depth courses on advanced image processing, machine learning and practical applications of computer vision. The course content includes basic image processing techniques, edge detection, image segmentation, feature extraction and an introduction to object recognition.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Have knowledge of image processing using traditional methods.	CLO1: Have knowledge of image and video processing, image transformations.	PLO7, 8
	CLO2: Analyze and extract information from images using traditional methods.	PLO7, 8
Skill
CO2: Master the OpenCV library	CLO3: Proficient in OpenCV image processing library.	PLO7, 8
CO3: Teamwork	CLO4: Have teamwork and presentation skills.	PLO9,10, 12
Self-control and responsibility
CO4: Be responsible for yourself and your work	CLO5: Be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Richard Szeliski (2022). Computer Vision: Algorithms and Applications . Springer.

Reference

[1] Forsyth, David A (2003). Computer Vision: A Modern Approach . Prentice-Hall of India.

[2] OpenCV Documentation (Online Documentation).

[3] Scikit-image Documentation (Online Documentation).

[4] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO4	10%
2	– Practice.	Rubric AM9	CLO1- CLO5	10%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO5	30%
II	Final assessment (end of term)
	– Students do group projects to perform image/video transformations for a real-world application.	Rubric AM8b	CLO1- CLO5	50%

(Appendix – Assessment Rubric attached)

CS334V: Natural Language Processing

General information about the course

Course name:				Course code: CS334V
Vietnamese Name: Natural Language Processing English Name: Introduction to Natural Language Processing
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS111V, CS202V, MATH110V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

Natural Language Processing (NLP) course introduces the fundamental concepts, techniques and algorithms in the field of human language processing by computers. NLP plays a pivotal role in many modern applications such as information retrieval, sentiment analysis, machine translation, chatbots and more. This course provides students with a solid foundation in text processing methods, parsing, semantics and practical applications of NLP. The course is closely related to the courses of Artificial Intelligence, Machine Learning, Data Mining and Statistics. The content includes text preprocessing, word representation, language modeling, parsing and common NLP applications.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Know and understand basic concepts and core problems in natural language processing.	CLO1: Explain the history, problems and applications of NLP.	PLO6, 7a, 7b
Skill
CO2: Apply NLP algorithms and techniques to solve practical problems.	CLO2: Perform text preprocessing, including tokenization, normalization, and stop word removal. Build word representation models such as Bag of Words, TF-IDF, and Word embeddings.	PLO8, 9
	CLO3: Build and evaluate n-gram language models. Apply parsing techniques such as Parsing and Dependency Parsing.	PLO8, 9
CO3: Use programming tools and libraries to build NLP applications.	CLO4: Use NLP libraries like NLTK, spaCy and Transformers in Python.	PLO8, 9
	CLO5: Design and implement a complete NLP system to solve a specific problem. Evaluate the performance of the built NLP system using appropriate metrics (respectively.	PLO8, 9
CO4: Teamwork, reporting and presentation skills.	CLO6: Have effective and persuasive teamwork, reporting and presentation skills. Work effectively in a team (if it is a group project), manage time and resources to complete the project on time.	PLO10, 12
Self-control and responsibility
CO5: Ability to self-study, research and update new knowledge in the field of NLP.	CLO7: Actively learn and update new technologies in the field of big data.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Walker, Adrian, (1990). Knowledge systems and Prolog : developing experts, databases, and natural language systems. Addison-Wesley.

Reference

[1] Bird, S., Klein, E., & Loper, E., (2009), Natural Language Processing with Python , O’Reilly Media Inc.

[2] Brownlee, J., (2016), Deep Learning for Natural Language Processing , Machine Learning Mastery. Link: https://machinelearningmastery.com/deep-learning-for-nlp/

[3] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO7	10%
2	– Practice.	Rubric AM9	CLO1- CLO7	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO2- CLO6	20%
II	Final assessment (end of term)
1	Students will undertake an NLP project in groups, applying the knowledge they have learned to solve a specific problem. Students will be assessed based on project reports and presentations.	Rubric AM8b	CLO1- CLO7	50%

(Appendix – Assessment Rubric attached)

CS364V: Application Security and Encryption

General information about the course

Course name:				Course code: CS364V
Vietnamese Name: Application Security and Encryption English Name: Cryptography and Secure Application
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : MATH201V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Ta Anh Phuong

–

phuong.ta@ttu.edu.vn

In charge

Brief description of course content

Applied Cryptography and Security course provides a solid foundation in modern cryptographic principles and techniques, as well as their applications in building secure systems. The course equips students with knowledge of symmetric and asymmetric encryption algorithms, hash functions, digital signatures, public key infrastructure (PKI), and security protocols. This course is an important foundation for more in-depth courses in information security and network security, and is closely related to courses in computer networks and programming. The course content includes basic concepts of cryptography, encryption algorithms, attack and defense methods, as well as practical applications of cryptography in system and data security.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand and master basic concepts, principles and algorithms in cryptography and information security.	CLO1: Explain basic concepts of information security (confidentiality, integrity, authenticity, non-repudiation) and distinguish common types of security attacks.	PLO4, 5
	CLO2: Describe and compare symmetric and asymmetric encryption algorithms, including the advantages, disadvantages and applications of each.	PLO4, 5
	CLO3: Describe the operating principles of hash functions, digital signatures, digital certificates and popular security protocols such as SSL/TLS, IPsec.	PLO4, 5
Skill
CO2: Apply acquired knowledge to analyze, evaluate and deploy information security systems.	CLO4: Use cryptographic tools and libraries to perform encryption, decryption, hash function calculations, and digital signature creation.	PLO8, 9
	CLO5: Analyze and evaluate the security of a simple information system, identify potential weaknesses.	PLO8, 9
	CLO6: Implement a basic security system, apply appropriate cryptographic algorithms and protocols, and implement common attack prevention measures.	PLO8, 9
CO3: Develop teamwork, reporting and presentation skills in the field of information security.	CLO7: Have effective teamwork skills, coordinate well with members and complete assigned tasks in the project.	PLO12
	CLO8: Have the ability to construct and present clear, complete and accurate technical reports on cryptographic and security related issues.	PLO10
Self-control and responsibility
CO4: Develop self-learning ability, sense of responsibility and professional ethics in the field of information security.	CLO9: Ability to self-study, proactively search and update information about new technologies and trends in the field of cryptography and security.	PLO14
	CLO10: Be responsible for work, comply with regulations on information security and professional ethics in the field.	PLO13, 15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

CLO10

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Carr, Houston H, (2007). Data communications and network security . McGraw-Hill

Reference

[1] Stallings, W. (2017). Cryptography and Network Security: Principles and Practice (7th Edition) . Pearson Education.

[2] Schneider, B. (1996). Applied Cryptography: Protocols, Algorithms, and Source Code in C (2nd Edition) . John Wiley & Sons

[3] Phan Dinh Dieu. (2002). Cryptography theory and information security . Hanoi National University Publishing House.

[4] Stuttard, D., & Pinto, M. (2011). The Web Application Hacker’s Handbook: Finding and Exploiting Security Flaws (2nd Edition) . Wiley.

[5] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO9	10%
2	– Practice.	Rubric AM9	CLO1- CLO6	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO10	20%
III	Final assessment (end of term)
	– Students will undertake a practical project involving cryptography and application security.	Rubric AM8b	CLO1- CLO10	50%

(Appendix – Assessment Rubric attached)

CS401V: Distributed Systems

General information about the course

Course name:				Course code: CS401V
Vietnamese Name: Distributed System English Name: Distributed Systems
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS205V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Truong Huu Tram

–

tram.truong-huu@ttu.edu.vn

In charge

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

Teaching Assistant

Brief description of course content

The growing development of information technology such as Wireless Sensor Network and Internet of Things has led to the collection of large amounts of data and information from the environment as well as human-environment interactions every day. This huge amount of data needs to be processed and returned within a limited period of time. Software and applications that process data sequentially become barriers and cannot meet the increasing demands of users. Distributed systems provide a way to connect and utilize computing and storage resources from computers distributed in different geographical locations to perform computing and data analysis tasks. The Distributed Systems course introduces the basic concepts of distributed systems, methods for designing and implementing fault-tolerant and scalable systems.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic concepts, operating principles and core issues in distributed systems.	CLO1: Explain the concepts of distributed systems, types of distributed systems, challenges and problems in distributed systems.	PLO3-6, 7c
	CLO2: Describe distributed architectural models (client-server, P2P, cloud computing) and the characteristics of each model.	PLO3-6, 7c
CO2: Apply inter-process communication, synchronization, data consistency, and error management techniques in a distributed environment.	CLO3: Present inter-process communication methods (sockets, RPC, RMI), synchronization algorithms, data consistency models and error management techniques in distributed systems.	PLO3-6, 7c
Skill
CO3: Analyze, design and deploy simple to complex distributed applications using modern distributed programming models and technologies.	CLO4: Build simple distributed applications using network programming technologies (sockets, RMI).	PLO8, 9
	CLO5: Apply synchronization techniques, data consistency management, and error handling in distributed applications	PLO8, 9
CO4: Evaluate and select appropriate solutions for specific problems in distributed systems.	CLO6: Analyze and compare different solutions for a specific problem in a distributed system, choose the optimal solution	PLO8, 9
CO5: Soft skills development	CLO7: Work effectively in a team, assign tasks and coordinate with other members to complete projects.	PLO12
Self-control and responsibility
CO6: Develop teamwork skills, critical thinking and self-learning ability during project implementation.	CLO8: Actively search, research documents and update new knowledge about distributed systems.	PLO14
	CLO9: Have a high sense of responsibility at work.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Tanenbaum, A.S., & Van Steen, M. (2007). Distributed systems: principles and paradigms (2nd ed. ). Pearson Prentice Hall.

Reference

[1] Birman, Kenneth P. (2012). Guide to Reliable Distributed Systems: Building High-Assurance Applications and Cloud-Hosted Services . Springger.

[2] Coulouris, G., Dollimore, J., Kindberg, T., & Blair, G. (2011). Distributed systems: concepts and design (5th ed.) . Addison-Wesley.

[3] Bal, Henr (1992). Programming Distributed Systems . Silicon Press.

[4] Brian Goetz, Tim Peierls, Joshua Bloch, Joseph Bowbeer, David Holmes, and Doug Lea, (2006). Java Concurrency in Practice .. Addison-Wesley Professional.

[5] Scott Oaks and Henry Wong, (2004). Java Threads , 3rd Edition. O’Reilly Press.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Be diligent and submit assignments on time.	Rubric AM1	CLO9	5%
2	– Document analysis.	Rubric AM7	CLO1,2,3,7,8,9	15%
3	– Practice exercises.	Rubric AM2a	CLO4-CLO9	40%
II	Final assessment (end of term)
1	– Subject group project.	Rubric AM8b	CLO1-CLO9	40%

(Appendix – Assessment Rubric attached)

CS408V: Software Project

General information about the course

Course name:				Course code: CS408V
Vietnamese Name: Software Project English Name: Software Project
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : Basic knowledge of programming and software engineering (See Academic Advisor)
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

–

dung.cao@ttu.edu.vn

In charge

Brief description of course content

Software Project course plays an important role in equipping students with practical skills and basic knowledge to manage and implement software projects from planning, requirements analysis to implementation and maintenance. This is a specialized course closely linked to subjects such as Programming, Software Engineering, and IT Project Management. The content includes project management techniques, software development methods, teamwork, documentation and practice of the entire software project life cycle through practical exercises and final projects.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Know and understand software project phases, project management techniques, software development methodologies and the relationship between project management, software engineering and IT project management.	CLO1: Know the phases of a software project from planning, requirements analysis, development, implementation to maintenance.	PLO7c
	CLO2: Explain key project management techniques and software development methodologies.	PLO7c
	CLO3: Analyze the relationship between project management, software engineering and IT project management.	PLO7c
Skill
CO2: Apply project management tools, create software documentation and work in teams to implement complete software projects.	CLO4: Apply project management tools and techniques to plan projects.	PLO8
	CLO5: Create software project products, such as requirements documents, UML diagrams, and technical documentation.	PLO7c
	CLO6: Work in teams to implement and present a complete software project.	PLO12
	CLO7: Writing reports and presentations.	PLO10
Self-control and responsibility
CO3: Form a habit of lifelong learning and update new technology.	CLO8: Ability to learn and update new technologies in the field of software technology.	PLO14
CO4: Diligent and proactive in work.	CLO9: Be self-aware and proactive in assigned work.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ghezzi, Carlo, Mehdi Jazayeri, Dino Mandrioli, (2003). Fundamentals of software engineering, 2nd edition , Prentice Hall, Pearson Education.

Reference

[1] Ian Sommerville, (2015), Software Engineering, 9th edition , Addison-Wesley

[2] Ken Schwaber, (2004) . Agile Project Management with Scrum, Microsoft Press .

[3] Tools: Git, Trello/JIRA, Visual Studio Code, Postman.

[4] Online platforms: GitHub, Stack Overflow, Medium (for technical blog posts).

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubrics AM1	CLO8	10%
2	– Group presentation (according to course project progress).	Rubric AM8b	CLO1,2,3,9	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO9	20%
II	Final assessment (end of term)
1	– Do group projects (write code, write reports, present, demo code).	Rubric AM8b	CLO1- CLO9	50%

(Appendix – Assessment Rubric attached)

CS411V: Big Data

General information about the course

Course name:				Course code: CS411V
Vietnamese Name: Big Data English Name: Big Data
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisite *(if any)* : CS311V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

0983695166

dung.cao@ttu.edu.vn

In charge

Pham Tran Thi Thu Ngan

–

Teaching assistant (if any)

Brief description of course content

Big Data course provides a foundational understanding of big data and cloud computing: its properties, characteristics, data sources, applications, and value. The course will cover distributed programming models (i.e., MapReduce) and big data management systems (both SQL and NoSQL) for big data applications. The course focuses more on hands-on experience with storage systems (Hadoop), big data processing on Spark, and orchestration with Airflow and Redis Queue. The course also introduces public cloud services such as AWS, Cloudera, and deployment solutions for big data applications on the cloud.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic concepts of big data, its characteristics, origins, applications and value.	CLO1: Define and distinguish concepts related to big data.	PLO6, 7a, 7b
	CLO2: Analyze the characteristics and applications of big data in different fields.	PLO6, 7a, 7b
Skill
CO2: Proficiency in distributed programming with MapReduce and using SQL, NoSQL and column-based database systems in big data processing.	CLO3: Build MapReduce programs to process distributed data.	PLO8, 9
	CLO4: Use SQL, NoSQL, and column-based queries to query and process big data.	PLO8, 9
CO3: Proficiently apply Hadoop, HDFS, YARN, Spark, Spark Streaming and Spark SQL technologies to build and deploy big data processing applications.	CLO5: Install and configure Hadoop and Spark environments.	PLO8, 9
	CLO6: Develop big data processing applications using Spark and Spark SQL.	PLO8, 9
	CLO7: Build real-time streaming data processing applications using Spark Streaming.	PLO8, 9
CO4: Have effective teamwork skills in real projects.	CLO8: Work effectively in groups on practical projects and final projects.	PLO12
CO4: Have effective teamwork skills in real projects.	CLO9: Present and defend project results clearly and convincingly.	PLO10
reliance and responsibility
CO5: Ability to self-study, learn and apply new technologies in the field of big data.	CLO10: Actively learn and update new technologies in the field of big data.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

CLO10

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] EMC Education Services (2015). Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data . John Wiley & Sons

Reference

[1] Rudy Lai and B. Potaczek (2019). Hands-On Big Data Analytics with PySpark. Packt Publishing

[2] Viktor Mayer-Schönberger and Kenneth Cukier (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.

[3] Aggarwal, CC (2015). Data Mining: The Textbook . Springer.

[4] Mohammed J. Zaki, Wagner Meira, Jr, (2020). Data Mining and Machine Learning: Fundamental Concepts and Algorithms. Cambridge University

[5] Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2nd Edition). O’Reilly Media.

[6] VanderPlas, J. (2016). Python Data Science Handbook . O’Reilly Media.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
	– Diligent and active in class.	Rubric AM1 and Rubric AM9	CLO10	10%
	– Individual exercise	RubricAM2a	CLO1,2, 3,4,5,6	40%
III	Final assessment (end of term)
	– Project: Students will undertake a real-world project involving big data processing and analysis, applying the knowledge and skills learned throughout the course. The project could be social media data analysis, server log data analysis, e-commerce data analysis, or other projects as directed by the instructor.	Rubric AM8b	CLO1 -10	50%

(Appendix – Assessment Rubric attached)

CS412V: Information Extraction and Web Searching

General information about the course

Course name:				Course code: CS412V
Vietnamese Name: Extract information and search on the Web English Name: Information Retrieval and Web Search
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS311V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Hoang Anh

–

anh.hoang@ttu.edu.vn

In charge

Brief description of course content

Information Extraction and Web Search course equips students with the knowledge and skills needed to build information retrieval systems from text and the web, which play an important role in fields such as Computer Science, Data Science, and Natural Language Processing. The course content includes the basic principles of information retrieval, models such as Boolean, vector space, and machine learning; text indexing techniques, system evaluation, clustering, document classification, and result ranking. In particular, the course delves into practical applications in web searching such as data collection, PageRank algorithm, and metadata analysis. This course is closely linked to subjects such as Natural Language Processing, Machine Learning, and Databases, creating a foundation for the development of intelligent information systems.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Have knowledge of information retrieval systems from text and web.	CLO1: Have knowledge of building document/information indexes.	PLO7
	CLO2: Have knowledge of document/information vectorization methods.	PLO7
Skill
CO2: Build a simple system to retrieve information from text and web.	CLO3: Apply available algorithms, methods, and tools to information storage and indexing problems to retrieve information.	PLO8
	CLO4: Apply tools to collect and store data from the Web.	PLO8
CO3: Teamwork, reporting and presentation skills.	CLO5: Have the ability to work in a team, present, and write clear and convincing reports.	PLO10, 12
reliance and responsibility
CO4: Diligent and proactive in work	CLO6: Be self-aware and proactive in assigned work.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] C. Manning, P. Raghavan, and H. Schütze, (2008). Introduction to Information Retrieval . Cambridge University Press, 2008.

Reference

Are not

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO6	10%
2	– Midterm test: multiple choice (50%) and essay (50%).	According to the answer	CLO1-CLO4	20%
3	– Group presentation.	Rubric AM8b	CLO1-CLO4	20%
II	Final assessment (end of term)
1	– Do group projects (write reports and give presentations).	Rubric AM8b	CLO1-CLO5	50%

(Appendix – Assessment Rubric attached)

CS413V: Data Processing

General information about the course

Course name:				Course code: CS413V
Vietnamese Name: Data Processing English Name: Data Preprocessing/cleansing
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS311V, CS332V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

Data Processing ” course provides an important foundation in data science, helping students master the techniques of data normalization, cleaning and transformation to ensure quality before analysis. This course is closely related to subjects such as Data Mining, Machine Learning and Artificial Intelligence, creating a foundation for effective data processing and exploitation. The content includes methods for handling missing data, errors, noise, duplicates, restructuring and data optimization, combined with intensive practice and final projects.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Have general knowledge of data processing in various formats.	CLO1: Have knowledge of data processing in the following cases: imbalance, noise, missing, duplication.	PLO7
	CLO2: Have knowledge of transforming (normalizing, cataloging, one-hot) data to suit the corresponding machine geometry subjects.	PLO7
Skill
CO2: Use and select tools and libraries for different data processing purposes.	CLO3: Proficiently use and select libraries (Scikit-learn, Imbalance), tools and methods (SMOTE, MICE, PCA,…) for data processing purposes.	PLO8
CO3: Teamwork, reporting, effective presentation.	CLO4: Have skills in teamwork, reporting, creating presentations, and giving convincing and effective presentations.	PLO10, 12
reliance and responsibility
CO4: Be responsible for yourself and your work	CLO5: Attend all classes; Be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2nd Edition). O’Reilly Media.

Reference

[1] VanderPlas, J. (2016). Python Data Science Handbook . O’Reilly Media.

[2] Wickham, H., & Grolemund, G. (2016). R for Data Science . O’Reilly Media.

[3] Aggarwal, CC (2015). Data Mining: The Textbook . Springer.

[4] Mohammed J. Zaki, Wagner Meira, Jr, (2020). Data Mining and Machine Learning: Fundamental Concepts and Algorithms . Cambridge University.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
	– Diligent and active in class.	Rubric AM1	CLO5	10%
	– Homework (individual).	Rubric AM2b	CLO1- CLO5	10%
	– Midterm test: Individual practice exercises.	AM3 Rubric	CLO1- CLO4	30%
III	Final assessment (end of term)
	– Students work on projects in groups. Reporting and presenting results is a mandatory requirement for final assessment.	Rubric AM8b	CLO1- CLO5	50%

(Appendix – Assessment Rubric attached)

CS414V: Data Science Project and Implementation

General information about the course

Course name:				Course code: CS414V
Vietnamese Name: Data Science Project and Implementation English Name: Data Science project and deployment
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : Basic knowledge of programming and software engineering (See Academic Advisor)
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

The course ” Data Science Project and Implementation ” equips students with comprehensive knowledge and practical skills to complete a complete Data Science project, from collection, pre-processing, analysis, model building and evaluation, to implementation, connecting learned theory with practice, helping students master the workflow of a Data Scientist. This is an intensive practical course for the final stage of the Data Science program, after students have a foundation in Mathematics, Statistics, Programming, Data Mining and Machine Learning. The content includes: project management, project development process, real data processing and analysis, machine learning model building and evaluation, model implementation, teamwork and presentation. The course is closely related to Advanced Mathematics, Applied Statistics (mathematical and statistical foundations), Python/R Programming (programming tools), Databases (data management and querying) and Data Mining, Machine Learning (algorithms and data analysis models). The main content revolves around: problem selection, data collection and preprocessing, data analysis and exploration, model building and evaluation, model deployment and project reporting.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Synthesize relevant knowledge for a data science problem.	CLO1: Know and understand the process of doing data science problems, including: problem setting, data identification, data collection and processing, data transformation, machine learning model building, and deployment into applications.	PLO3-7
Skill
CO2: Summary of skills required for data science related jobs.	CLO2: Have skills to collect and process data for data science problems.	PLO8
	CLO3: Have skills in data analysis and mining.	PLO8
	CLO4: Evaluate machine learning models and deploy them into applications.	PLO8
CO3: Teamwork skills, reporting, effective, clear and convincing presentation.	CLO5: Have the ability to work in a team, report, and present effectively, clearly, and convincingly.	PLO10, 12
Self-control and responsibility
CO4: Be responsible for yourself and your work	CLO6: Attend all classes; Be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] EMC Education Services, (2015). Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data . John Wiley & Sons.

Reference

[1] Andriy Burkov. (2020). Machine Learning Engineering , True Positive Inc.

[2] Jake VanderPlas (2017). Python Data Science Handbook: Essential Tools for Working with Data . O’reilly.

[3] Sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO4	10%
2	– Midterm test: Individual practice exercises.	AM3 Rubric	CLO1- CLO6	30%
II	Final assessment (end of term)
1	– Do projects (write code and present).	Rubric AM8b	CLO1- CLO6	60%

(Appendix – Assessment Rubric attached)

CS431: Advanced Machine Learning

General information about the course

Course name:				Course code: CS431V
Vietnamese Name: Advanced Machine Learning English Name: Advanced Machine Learning
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS332V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

0983 695 166

dung.cao@ttu.edu.vn

In charge

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

Join

Brief description of course content

Advanced Machine Learning ” course continues to equip students with in-depth knowledge of modern machine learning methods, complementing the knowledge learned in the basic courses. The course focuses on three main topics: probability-based learning methods (with an emphasis on Bayesian theory and Bayesian networks), ensemble learning methods (including bagging and boosting techniques), and time series data processing. This course plays an important role in preparing students to research and apply advanced machine learning techniques to solve complex real-world problems.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Deeply understand the principles and algorithms of probability-based learning, ensemble learning, and time series data processing.	CLO1: Explain the basic concepts of Bayesian theory, Bayesian networks, bagging and boosting methods, and time series data processing techniques.	PLO6, 7a, 7b
	CLO2: Analyze and compare the advantages and disadvantages of advanced machine learning algorithms.	PLO6, 7a, 7b
Skill
CO2: Proficiently apply advanced machine learning techniques to solve real-world problems, especially with time series data.	CLO3: Build and deploy machine learning models based on learned techniques using appropriate libraries and programming tools.	PLO8, 9
	CLO4: Evaluate and select appropriate machine learning models for each specific problem.	PLO8, 9
CO3: Ability to work in groups, report and present effectively in projects.	CLO5: Work effectively in a team to complete a project, assign tasks and coordinate well with team members. Present and defend project results clearly and convincingly.	PLO10, 12
reliance and responsibility
CO4: Ability to self-study, learn and update new knowledge in the field of machine learning.	CLO6: Actively seek and synthesize information from different sources to solve problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Barber, David, (2022). Bayesian reasoning and machine learning . Cambridge Uni. Press

Reference

[1] Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2nd Edition). O’Reilly Media.

[2] Bell, Jason (2020). Machine learning: hands-on for developers and technical professionals . Wiley.

[3] Murphy, K.P. (2012). Machine learning: a probabilistic perspective . MIT press.

[4] Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media.

[5] Hyndman, RJ, & Athanasopoulos, G. (2021). Forecasting: principles and practice . OTexts. (Time series literature)

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
	– Attendance/discussion/homework.	Rubric AM1, AM2a, AM2b	CLO1-CLO6	10%
1	– Midterm test: Multiple choice.	According to the test scale	CLO1-CLO6	20%
2	– Regular test: Presentation//Question and answer.	AM3 Rubric	CLO1-CLO6	20%
II	Final assessment (end of term)
1	– Project: Students will carry out a group project, applying the knowledge they have learned to solve a practical problem related to advanced machine learning, especially time series data processing. The project is encouraged for students to choose their own topic or can be suggested by the lecturer.	Rubric AM8a, AM8b	CLO1-CLO6	50%

(Appendix – Assessment Rubric attached)

CS434V: Deep Learning

General information about the course

Course name:				Course code: CS434V
Vietnamese Name: Deep Learning English Name: Deep Learning
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS332V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

0983 695 166

dung.cao@ttu.edu.vn

In charge

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

Join

Brief description of course content

Deep Learning course introduces deep learning. Deep learning has attracted significant attention in the industry due to its state-of-the-art results in computer vision and natural language processing. Students will learn the fundamentals and advanced techniques of deep learning, as well as modern techniques for building advanced models such as CNN, RNN, LSTM, Autoencoder, VAE, GAN, U-Net, Transformer, etc. Students will use TensorFlow/PyTorch and Keras API to build deep learning models.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Know and understand the basic concepts of deep learning and types of neural networks.	CLO1: Explain the difference between machine learning and deep learning. Describe the structure and operating principles of basic neural networks (e.g. Perceptron, MLP).	PLO7a, 7b
	CLO2: Analyze and compare the advantages and disadvantages of advanced machine learning algorithms.	PLO7a, 7b
Skill
CO2: Build and train deep learning models using TensorFlow and PyTorch.	CLO3: Use TensorFlow/Keras and PyTorch to build CNN, RNN, Autoencoder, VAE, GAN models	PLO8, 9
	CLO4: Apply optimization methods and hyperparameter tuning to improve model performance.	PLO8, 9
CO3: Apply deep learning to solve real-world problems in computer vision and natural language processing.	CLO5: Build applications for image recognition, text classification, image generation using GAN, etc.	PLO8, 9
	CLO6: Evaluate and analyze model results.	PLO8, 9
CO4: Grasp the latest trends and research in the field of deep learning.	CLO7: Research and present scientific articles on deep learning.	PLO8, 9
	CLO8: Assess the application potential of new deep learning techniques.	PLO8, 9
CO5: Ability to work in a team and make effective presentations in projects.	CLO9: Work effectively in a team to complete projects, assign tasks and coordinate well with team members.	PLO12
	CLO10: Present and defend project results clearly and convincingly.	PLO10
reliance and responsibility
CO6: Ability to self-study, learn and update new knowledge in the field of deep learning.	CLO11: Actively seek and synthesize information from different sources to solve problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

CLO9

CLO10

CLO11

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Ian Goodfellow, Yoshua Bengio, Aaron Courville. (2016). Deep Learning . MIT Press.

[2] Charniak, Eugene (2018). Introduction to deep learning. MIT Press.

Reference

[1] Aurélien Géron. (2019). Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow . O’Reilly Media.

[2] François Chollet. (2017). Deep Learning with Python . Manning Publications.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
	– Diligent and active in class.	Rubric AM1	CLO10,11	10%
	– Individual exercise.	Rubric AM2a	CLO1,2, 3,4,5,6	40%
III	Final assessment (end of term)
	– Project: Students will undertake a real-world project that applies the knowledge learned in the course. The project may involve computer vision (e.g., object recognition, image classification), natural language processing (e.g., machine translation, sentiment analysis), or other areas.	Rubric AM8b	CLO1-CLO10	50%

(Appendix – Assessment Rubric attached)

CS435V: Deep Learning Practice in Natural Language Processing

General information about the course

Course name:				Course code: CS435V
Vietnamese Name: Deep Learning Practice in Language Processing English name: Practical Deep learning in Natural Language Processing
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS434V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

Deep Learning in Language Processing Practical course equips students with in-depth knowledge and practical skills in applying deep learning to the field of natural language processing (NLP). This course plays an important role in connecting deep learning theory with practical NLP problems, enabling students to build and deploy advanced NLP systems. The course is closely related to the courses on Natural Language Processing, Machine Learning, and Deep Learning. The course content includes text preprocessing techniques, popular deep neural network models in NLP (RNN, LSTM, GRU, Transformer), and their applications in tasks such as sentiment analysis, machine translation, question answering, and text summarization.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master deep learning concepts, deploy and fine-tune advanced NLP models, and evaluate and improve their performance.	CLO1: Understand the basic concepts of deep learning and their applications to natural language processing tasks.	PLO1, 3-7
	CLO2: Know how to implement and fine-tune advanced NLP models like RNN, LSTM, GRU and Transformer using popular deep learning frameworks Tensorflow/Pytorch.	PLO1, 3-7
	CLO3: Know how to evaluate the performance of NLP models and implement techniques to improve their accuracy and efficiency.	PLO1, 3-7
Skill
CO2: Equip yourself with the skills to solve real-world NLP challenges, research information to solve problems, and work in teams to discuss and present.	CLO4: Solve real-world NLP challenges, such as text analysis, classification, machine translation, and text summarization.	PLO8
	CLO5: Search and read necessary information to solve the problem being faced; Have teamwork skills (discussion and presentation, report presentation).	PLO9, 10, 12
Self-control and responsibility
CO3: be responsible for yourself and your work	CLO6: Attend all classes; Be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

WORRY

PLO8

WORRY

PLO11

WORRY

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Walker, Adrian, (1990). Knowledge systems and Prolog: Developing expert, Database, and Natural language systems . Addison-Wesley.

Reference

[1] Bird, S., Klein, E., & Loper, E., (2009), Natural Language Processing with Python , O’Reilly Media Inc.

[2] Brownlee, J., (2016). Deep Learning for Natural Language Processing , Machine Learning Mastery. Link: https://machinelearningmastery.com/deep-learning-for-nlp/

[3] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO6	10%
2	– Practice.	Rubric AM9	CLO1- CLO6	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO6	20%
II	Final assessment (end of term)
	– Students carry out a real NLP project, applying the knowledge learned in the course. Assessment is based on project reports and presentations.	Rubric AM8b	CLO1- CLO6	50%

(Appendix – Assessment Rubric attached)

CS436V: Deep Learning Practice in Computer Vision

General information about the course

Course name:				Course code: CS436V
Vietnamese Name: Deep Learning Practice in Computer Vision English Name: Practical Deep learning in Computer Vision
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 01	Number of practice credits: 02		Number of internship credits: 00
Number of theory lessons: 15		Number of practice sessions: 60
Number of practice hours: 00		Number of self-study hours: 60
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : CS333V, CS434V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Nguyen Xuan Ha

–

ha.nguyen@ttu.edu.vn

In charge

Brief description of course content

The course ” Deep Learning in Computer Vision Practice ” provides students with in-depth knowledge and practical skills in applying deep learning in the field of computer vision. This course focuses on building, training and deploying deep learning models for common computer vision problems such as image classification, object detection, image segmentation and image generation. This course is a logical continuation of the subjects on image processing, computer vision and machine learning, equipping students with a solid foundation for researching and developing advanced computer vision applications. The course content includes neural network architectures Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs) and advanced training techniques.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: have in-depth knowledge of the following learning models for image and video data.	CLO1: Understand deep learning models for computer vision: CNN, YOLO, ResNet, Fast R-CNN, GAN, U-Net.	PLO3-7
	CLO2: Understand data augmentation techniques when training deep learning models.	PLO3-7
CO2: Proficiency in frameworks and libraries.	CLO3: Proficient in using deep learning platforms such as: Tensorflow/Pytorch and OpenCV library.	PLO3-7
CO3: Take advantage of pre-trained models.	CLO4: Use available architectures for problems of object recognition, image and video classification.	PLO3-7
CO3: Take advantage of pre-trained models.	CLO5: Use open (trained) models and transfer learning methods to serve specific problems.	PLO3-7
Skill
CO4. Select the appropriate solution for each specific practical problem.	CLO6: Select available architectures for real-world object recognition, image and video classification problems	PLO9
CO5: Teamwork, reporting and presentation skills.	CLO7: Have teamwork, reporting and persuasive presentation skills.	PLO10, 12
Self-control and responsibility
CO6: Be responsible for yourself and your work.	CLO8: Actively participate in class sessions; be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15	CLO1	3	3	3	3	3
CLO2			3	3	3	3	3
CLO3			3	3	3	3	3
CLO4			3	3	3	3	3
CLO5			3	3	3	3	3
CLO6									3
CLO7										4		4
CLO8															4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Richard Szeliski (2022). Computer Vision: Algorithms and Applications . Springer.

Reference

[1] Forsyth, David A (2003). Computer Vision: A Modern Approach . Prentice-Hall of India.

[2] Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning . MIT Press.

[3] OpenCV Documentation (Online Documentation).

[4] Scikit-image Documentation (Online Documentation).

[5] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO8	10%
2	– Practice.	Rubric AM9	CLO1- CLO8	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1- CLO8	20%
II	Final assessment (end of term)
1	– Students carry out a real computer vision project, applying the knowledge learned in the course. Assessment is based on project reports and presentations.	Rubric AM8b	CLO1- CLO8	50%

(Appendix – Assessment Rubric attached)

CS437V: Pattern Recognition

General information about the course

Course name:				Course code: CS437V
Vietnamese Name: Pattern Recognition English Name: Pattern Recognition
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : MATH110V, STA206V, CS331V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Cao Tien Dung

0983 695 166

dung.cao@ttu.edu.vn

In charge

Brief description of course content

Pattern Recognition is a specialized course in the field of Artificial Intelligence and Machine Learning. The course provides fundamental and in-depth knowledge of pattern recognition methods, from data preprocessing techniques, feature extraction to classification algorithms and performance evaluation. The course equips students with the ability to analyze, design and deploy pattern recognition systems in many practical applications, including image, audio, natural language and tabular data processing. This course is closely related to subjects such as Linear Algebra, Calculus, Statistics, Machine Learning and Data Mining. The course content includes types of data patterns, feature extraction, classification models (Naive Bayes, SVM, LDA, PCA, ANN), and applications on audio, image, NLP and tabular data.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the basic concepts of pattern recognition.	CLO1: Define the concept of pattern, pattern recognition, and the basic stages of a pattern recognition system and the challenges of the problem.	PLO3-7
CO1: Understand the basic concepts of pattern recognition.	CLO2: Distinguish between types of pattern recognition problems (classification, regression, clustering). State typical applications of pattern recognition in different fields.	PLO3-7
CO2: Master feature extraction methods from different types of data (audio, image, NLP, tables).	CLO3: Describe and compare feature extraction methods for digital data (e.g. statistics, Fourier transform).	PLO3-7
	CLO4: Apply feature extraction techniques from images (eg: HOG, SIFT, SURF).	PLO3-7
	CLO5: Apply feature extraction methods to text data (e.g. Bag of Words, TF-IDF, word embeddings).	PLO3-7
CO3: Understand and apply popular classification algorithms (Naive Bayes, SVM, LDA, PCA, ANN, parametric and non-parametric models).	CLO6: Explain the working principle of the Naive Bayes algorithm and the conditions for its application. Distinguish between PCA and LDA and state the purpose of each algorithm.	PLO3-7
	CLO7: Describe the SVM optimization problem and the role of kernel trick.	PLO3-7
CO4: Teamwork skills, reporting, presentation, persuasive and effective.	CLO8: Have skills in teamwork, reporting, and presentation that are convincing and effective.	PLO10, 12
Skill
CO5: Analyze and select appropriate pattern recognition methods for each specific problem.	CLO9: Analyze and select appropriate pattern recognition methods for each specific problem.	PLO8
CO5: Build, train, and evaluate pattern recognition models using programming tools and libraries.	CLO10: Build, train, and evaluate pattern recognition models using programming tools and libraries.	PLO8
Self-control and responsibility
CO6: be responsible for yourself and your work	CLO11: Attend all classes; Be self-aware and proactive in completing assigned tasks.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15	CLO1	3	3	3	3	3
CLO2			3	3	3	3	3
CLO3			3	3	3	3	3
CLO4			3	3	3	3	3
CLO5			3	3	3	3	3
CLO6			3	3	3	3	3
CLO7			3	3	3	3	3
CLO8										3		3
CLO9								3
CLO10								3
CLO11															3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Christopher M. Bishop. (2006). Pattern Recognition and Machine Learning . Springer.

Reference

[1] Richard O. Duda, Peter E. Hart, David G. Stork. (2001). Pattern Classification . Wiley-Interscience.

[2] Ian Goodfellow, Yoshua Bengio, Aaron Courville. (2016). Deep Learning . MIT Press.

[3] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO9	10%
2	– Practice.	Rubric AM9	CLO1- CLO6	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO2- CLO6	20%
II	Final assessment (end of term)
4	Students will undertake a practical project related to Pattern Recognition , applying the knowledge learned to solve a specific problem. The project can be done in groups or individually, and will be evaluated based on creativity, application, and quality of the report.	Rubric AM8b	CLO1- CLO11	50%

(Appendix – Assessment Rubric attached)

CS440V: Computer Networks

General information about the course

Course name:				Course code: CS440V
Vietnamese Name: Computer Network English Name: Computer Network
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS205V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Dr. Truong Huu Tram

–

tram.truong-huu@ttu.edu.vn

In charge

Brief description of course content

Computer Networks course provides students with fundamental and in-depth knowledge of the structure, operation, and protocols of modern computer networks, with a particular focus on the Internet and the TCP/IP model. This course plays an important role in building foundational knowledge for more in-depth courses on network security, network administration, and network applications. Knowledge from this course also helps students have a foundation to approach international certificates such as CCNA. The course content includes layered network architecture, protocols from the physical layer to the application layer, routing, switching, and socket programming.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand the TCP/IP layered architecture and the functions of each layer.	CLO1: Explain the functions and interactions between layers in the TCP/IP model.	PLO7c
CO2: Master important network protocols such as IP, TCP, UDP, DNS, DHCP.	CLO2: Describe the operation of TCP, UDP, DNS, DHCP protocols and their roles in the network.	PLO7c
Skill
CO3: Configure and manage LANs, VLANs, and network devices such as switches and routers.	CLO3: Configure switches and routers to build LANs, VLANs and connect networks.	PLO8, 9
CO4: Analyze and solve basic network problems.	CLO4: Use network analysis tools to identify and troubleshoot network problems.	PLO8, 9
CO5: Programming network applications using sockets.	CLO5: Build simple network applications using socket programming.	PLO8, 9
CO7: Soft skills development (teamwork, project management).	CLO6: Work collaboratively to complete projects and share knowledge.	PLO12
	CLO7: Present and defend project results clearly and convincingly.	PLO10
Self-control and responsibility
CO6: Self-study, research and update new knowledge about computer networks.	CLO8: Proactively learn and apply new network technologies into practice.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Kurose, J.F., & Ross, K.W. (2017). Computer networking: A top-down approach . Pearson Education.

Reference

[1] Odom, Wendell. (2016). Cisco CCENT/CCNA ICND1 100-105 Official Cert Guide. Cisco Press.

[2] Odom, Wendell. (2017). Cisco CCNA Routing and Switching ICND2 200-105 Official Cert Guide . Cisco Press.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Analyze documents in groups and report.	AM3 Rubric	CLO6,7	20%
2	– Group project number 1 and report.	AM3 Rubric	CLO6,7,8	25%
3	– Group project number 2 and report.	AM3 Rubric	CLO6,7,8	25%
II	Final assessment (end of term)
1	– Final exam (multiple choice and essay).	According to the answer	CLO1-CLO8	30%

(Appendix – Assessment Rubric attached)

CS441V: Data Visualization

General information about the course

Course name:				Course code: CS441V
Vietnamese Name: Data Visualization English Name: Data Visualization
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS111V (Introduction to Computer Science and Python Programming)
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	In charge

Brief description of course content

Data visualization is the graphical representation of data, which plays an important role in representing data at both small and large scales. The main objective of this course is to provide skills to explore data, thereby revealing valuable information by extracting information, gaining insights from data and making effective decisions. In the course, various visualization libraries such as Matplotlib, Seaborn, ggplot, Plotly, Folium, etc. will be introduced.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master the supporting libraries in Python.	CLO1: Create visualizations to present data using different libraries like Matplotlib, Seaborn, ggplot, Plotly, Folium;	PLO3-7
CO2: Identify chart types for each visualization purpose.	CLO2: Identify the most appropriate chart for each specific problem	PLO3-7
	CLO3: Interpret data based on visualized charts/graphs. Present data in a way that is understandable to everyone.	PLO3-7
	CLO4: Analyze, evaluate, and edit data visualizations.	PLO3-7
Skill
CO4: Teamwork, presentation and information searching skills.	CLO5: Have teamwork and presentation skills.	PLO10, 12
	CLO6: Find and read information needed to solve a problem	PLO9
Level of autonomy and responsibility
CO5: Demonstrate a sense of professional responsibility and lifelong learning.	CLO7: Develop a sense of professional responsibility and the ability to self-study and lifelong learning to meet job requirements and develop oneself throughout one’s career.	PLO13, 14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7			PLO8	PLO9	PLO 10	PLO 11	PLO 12	PLO 13	PLO 14	PLO 15
	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	a	b	c	PLO8	PLO9	PLO 10	PLO 11	PLO 12	PLO 13	PLO 14	PLO 15
CLO1			4	4	4	4	5	4	4
CLO2			4	4	4	4	5	4	4
CLO3			4	4	4	4	5	4	4
CLO4			4	4	4	4	5	4	4
CLO5												4		4
CLO6											4
CLO7															3	3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

The course does not require any mandatory textbooks, some reference books will be introduced during the lessons.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	Homework (individual).	Rubik AM2a	CLO1-CLO7	30%
2	Midterm group project.	Rubik AM8b	CLO1-CLO7	30%
II	Final assessment (end of term)
1	Final group project.	Rubik AM8b	CLO1-CLO7	40%

(Appendix – Assessment Rubric attached)

CS447V: Reinforcement Learning

General information about the course

Course name:				Course code: CS447V
Vietnamese Name: Reinforcement Learning English Name: Reinforcement Learning
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 02	Number of practice credits: 01		Number of internship credits: 00
Number of theory lessons: 30		Number of practice sessions: 30
Number of practice hours: 00		Number of self-study hours: 75
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : CS434V
Course management department *(if any)* :

Information about the instructor

Academic title, academic degree,

Full name

Phone number

E-mail

Note

Assoc. Prof. Dr. Tran Vu Khanh

0989282522

khanh.tran@ttu.edu.vn

In charge

Brief description of course content

The course ” Reinforcement Learning ” introduces students to an important area of artificial intelligence, which focuses on training agents to make optimal decisions in an environment. This course equips students with knowledge of popular reinforcement learning algorithms, from basic to advanced, along with the ability to apply them to solve real-world problems. The course is closely related to courses such as Machine Learning, Artificial Intelligence, and Advanced Mathematics. The course content includes basic concepts of reinforcement learning, algorithms such as Q-learning, SARSA, Deep Q-Networks, and their applications in various fields.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Equip students with in-depth theoretical knowledge about reinforcement learning	CLO1: Understand and explain basic concepts of reinforcement learning.	PLO7
CO2: Help students understand the working principles of reinforcement learning algorithms	CLO2: Analyze the working principles of reinforcement learning algorithms such as Q-learning, SARSA, Deep Q-Networks.	PLO7
	CLO3: Identify the relationship between agent, environment, action and reward in reinforcement learning.	PLO7
Skill
CO3: Practice design skills, programming capacity, implementation, and evaluation of reinforcement learning models	CLO4: Design, program, implement and evaluate reinforcement learning models for real-world problems. Apply reinforcement learning knowledge to areas such as robotics, games, and intelligent control.	PLO8
CO4: Have teamwork, reporting and presentation skills.	CLO5: Have teamwork, reporting and presentation skills.	PLO10, 12
Self-control and responsibility
CO5: Form lifelong learning habits and update new technology	CLO6: Ability to learn and update new technology in the field of artificial intelligence.	PLO14
CO6: Diligent and proactive in work	CLO7: Be self-aware and proactive in assigned work.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

WORRY

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Richard S. Sutton and Andrew G. Barto (2018). Reinforcement learning: An introduction . The MIT Press.

Reference

[1] Csaba Szepesvári (2010), Algorithms for Reinforcement Learning . Morgan & Claypool Publishers.

[2] Other sources on the internet.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO8	10%
2	– Practice.	Rubric AM9	CLO3, 4	20%
3	– Midterm test: Multiple choice (50%) and practice (50%).	AM9 Test and Rubric	CLO1-CLO7	20%
II	Final assessment (end of term)
1	– Students will be required to carry out a project applying the knowledge they have learned to solve a specific problem, which can be a problem in a game, robotics, or another field (report, presentation, code, demo).	Rubric AM8b	CLO1-CLO7	50%

(Appendix – Assessment Rubric attached)

CS450V: Topics in Data Science

General information about the course

Course name:				Course code: CS450V
Vietnamese Name: Topics on Data Science English Name: Data Science topics
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 00	Number of practice credits: 03		Number of internship credits: 00
Number of theory periods: 00		Number of practice hours: 90
Number of practice hours: 00		Number of self-study hours: 45
Number of assessment/discussion periods: 00
Number of other activities:
Prerequisites *(if any)* : Consult Academic Advisor
Course management department *(if any)* :

Information about the instructor

TT	Academic title, academic degree, Full name	Phone number	E-mail	Note
1	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	In charge
2	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	Join
3	Dr. Tran Vu Khanh	–	khanh.tran@ttu.edu.vn	Join
4	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	Join

Brief description of course content

The course ” Topics in Data Science ” aims to equip students with in-depth and practical knowledge of techniques and applications in data science. The course is organized in the form of seminars, with the participation of guest experts from businesses and universities. Students are encouraged to conduct independent research, practice in groups and write final reports. The course provides a solid foundation for students when participating in subsequent courses or applying in their careers.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Provide in-depth knowledge of topics in data science	CLO1: Understand and master basic and advanced techniques and tools in data science, including data analysis, machine learning, big data mining, and practical applications.	PLO7a,b
CO1: Provide in-depth knowledge of topics in data science	CLO2: Understand new methods and trends in data science, such as deep learning, artificial intelligence (AI), and real-time data analytics.	PLO7a,b
Skill
CO2: Encourage independent research and study, teamwork skills.	CLO3: Have independent research skills and critical thinking to solve data science problems.	PLO8
	CLO4: Teamwork skills. Conduct detailed research reports on data science issues and communicate research results clearly and coherently.	PLO10, 12
Self-control and responsibility
CO3: Autonomy in work	CLO5: Be proactive in searching for documents, researching new data science problems and applying modern tools in research.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

There is no required curriculum.

Reference

[1] Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction . Springer.

[2] Provost, F., & Fawcett, T. (2013). Data Science for Business . O’Reilly Media.

[3] Bishop, CM (2006). Pattern Recognition and Machine Learning . Springer.

[4] McKinney, W. (2017). Python for Data Analysis . O’Reilly Media.

[5] https://365datascience.com/projects/

[6] Guest lectures depending on the time.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO1-CLO5	10%
2	– Group presentation by topic.	Rubric AM8b	CLO1-CLO5	40%
II	Final assessment (end of term)
	– Personal summary report on assigned topics.	Rubric AM7	CLO1-CLO5	50%

(Appendix – Assessment Rubric attached)

CS470V: Graduation Project

General information about the course

Course name:				Course code: CS470V
Vietnamese Name: Graduation Project English Name: Graduation Project
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major ☒ Graduation thesis/Project Supplement
Total credits: 08
Number of theoretical credits: 08	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 360		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 360
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite courses *(if any)* : Consult with Academic Advisor or instructor.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	Dr. Truong Huu Tram	–	tram.truong-huu@ttu.edu.vn	Co-in charge
3	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	Co-in charge

Brief description of course content

The Graduation Project is the final and comprehensive course in the training program, playing a key role in assessing the ability to apply learned knowledge to solve practical problems in the field of Information Technology. This course equips students with the skills to research, analyze, design, implement and evaluate a complete software system, data science or machine learning problem. The graduation project demonstrates the student’s ability to self-study, think creatively and work independently. The course is closely related to all previously studied specialized courses, especially courses on system analysis and design, programming, databases, data science and machine learning. The result of the course is a working demo program and a detailed report (or presentation slide). The project content is guided by the lecturer and chosen by the student and registered with the faculty.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Synthesize the knowledge learned.	CLO1: Apply specialized knowledge to solve a specific problem in the field of software, data science or machine learning.	PLO3-7
	CLO2: Understand the software development process or scientific research process.	PLO3-7
	CLO3: Understand the methods, technologies and tools related to the topic.	PLO3-7
Skill
CO2: Apply learned knowledge to specific problems.	CLO4: Analyze, design and deploy a software system or data science/machine learning solution. Proficient in programming tools, data analysis, machine learning and supporting technologies.	PLO8
	CLO5: Write scientific reports and present research results clearly, coherently and convincingly.	PLO9
	CLO6: Work independently, work in groups, report, present (if any) and manage time effectively.	PLO10, 12
Self-control and responsibility
CO3: Self-learning and lifelong learning capacity.	CLO7: Be proactive in searching for documents, researching and solving problems. Have a high sense of responsibility for work results.	PLO14
	CLO8: Comply with scientific ethics and copyright regulations.	PLO15
	CLO9: Ability to self-evaluate and adjust work processes.	PLO13

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4
CLO2			4	4	4	4	4
CLO3			4	4	4	4	4
CLO4								4
CLO5									4
CLO6										4		4
CLO7														4
CLO8															4
CLO9													4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Due to the diverse nature of project topics, references will be updated and supplemented according to each specific topic. However, here are some general suggestions:

– About software development:

[1] Sommerville, I., (2016). Software Engineering , 10th Edition, Pearson Education Limited.
[2] Pressman, RS and Maxim, BR, (2015). Software Engineering: A Practitioner’s Approach , 8th Edition, McGraw-Hill Education.

– About Data Science and Machine Learning:

[3] Hastie, T., Tibshirani, R. and Friedman, J., (2009). The Elements of Statistical Learning , 2nd Edition, Springer.
[4] Bishop, CM, (2006). Pattern Recognition and Machine Learning , Springer.
[5] Géron, A., (2019). Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow , 2nd Edition, O’Reilly Media.

In addition, students need to actively search for scientific articles, online documents and other information sources related to their topic. The instructor will be responsible for assisting students in selecting appropriate reference materials.

Assessment of learning outcomes

Form and method of assessment

Assessment tools

Learning outcomes of the course

Weight

Product reviews, reports and protection

Evaluate the quality of the project (content, form, scientific nature, novelty, applicability…).

Evaluate students’ reporting quality, presentation skills, and question-answering abilities.

Rubric AM10c

CLO1-CLO9

100%

(Appendix – Assessment Rubric attached)

CS471V: Graduation Essay

General information about the course

Course name:				Course code: CS471V
Vietnamese Name: Graduation Essay English Name: Graduation Essay
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major ☒ Graduation thesis/Project Supplement
Total credits: 04
Number of theoretical credits: 04	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 180		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 540
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite courses *(if any)* : Consult with Academic Advisor or instructor.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	Dr. Truong Huu Tram	–	tram.truong-huu@ttu.edu.vn	Co-in charge
3	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	Co-in charge
4	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	Co-in charge
5	Assoc. Prof. Dr. Tran Vu Khanh	0989 282 522	khanh.tran@ttu.edu.vn	Co-in charge

Brief description of course content

Graduation Essay course is the final and important stage in the training program, allowing students to apply the knowledge and skills they have learned to conduct an in-depth study on a specific topic in the field of Computer Science, Data Science, Machine Learning or Software Systems. This course equips students with the skills of independent research, analysis, synthesis of information, writing scientific reports and presentations. It has a close relationship with previous specialized courses, providing a basis for students to continue studying at higher levels or participate in research and development activities. The course content includes choosing a topic, building an outline, collecting and processing data, analyzing results and writing reports.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Systematize learned knowledge and research a problem not yet in the curriculum.	CLO1: Understand scientific research methods or learn new technology.	PLO3-7
	CLO2: Understand the process of writing a graduate thesis.	PLO3-7
	CLO3: Deep understanding of a specific problem or new technology in the field of expertise.	PLO3-7
	CLO4: Build a demo program (if any).	PLO3-7
Skill
CO2: Practice self-study skills, search for documents, write reports, present problems.	CLO5: Search, read and synthesize scientific documents.	PLO9, 11
	CLO6: Analyze, evaluate and compare research projects or new technologies.	PLO9
	CLO7: Develop a research outline and conduct research. Write a report according to standards. Present and defend research results before a panel.	PLO10
Self-control and responsibility
CO3: proactive in work, adhere to research ethics.	CLO8: Proactive, creative and responsible in research.	PLO14
	CLO9: Have a spirit of cooperation and learning.	PLO13
	CLO10: Comply with scientific research ethics.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4
CLO2			4	4	4	4	4
CLO3			4	4	4	4	4
CLO4			4	4	4	4	4
CLO5									4		4
CLO6									4
CLO7										4
CLO8														4
CLO9													4
CLO10															4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Due to the diverse nature of project topics, references will be updated and supplemented according to each specific topic. However, here are some general suggestions:

[1] Dawson, Catherine (2009). Introduction to research methods: a practical guide for anyone undertaking a research project . Howtobooks

[2] Nguyen Dinh Tho (2012), Scientific research methods in business . Labor – Social Publishing House.

[3] Booth, W.C., Colomb, GG, & Williams, J.M. (2008). The craft of research. University of Chicago press.

[4] Scientific articles in specialized journals related to the topic.

[5] Published research works (theses, dissertations, theses).

[6] Faculty/school thesis writing guidelines.

Assessment of learning outcomes

Form and method of assessment

Assessment tools

Learning outcomes of the course

Weight

Process and product evaluation

– Evaluate students’ diligence, progress and work spirit throughout the essay writing process.

– Evaluate the quality of the essay (content, form).

Rubric AM10b

CLO1-CLO10

100%

(Appendix – Assessment Rubric attached)

CS480V: Graduation Thesis

General information about the course

Course name:				Course code: CS480V
Vietnamese Name: Graduation Thesis English Name: Graduation Thesis
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major ☒ Graduation thesis/Project Supplement
Total credits: 08
Number of theoretical credits: 08	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 360		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 360
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisites *(if any)* : Must consult with Academic Advisor, instructor and GPA at time of registration must be greater than or equal to 3.0.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	Dr. Truong Huu Tram	–	tram.truong-huu@ttu.edu.vn	Co-in charge
3	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	Co-in charge
4	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	Co-in charge
5	Assoc. Prof. Dr. Tran Vu Khanh	0989 282 522	khanh.tran@ttu.edu.vn	Co-in charge

Brief description of course content

Graduation Thesis course is the final, comprehensive and in-depth course in the training program. This course equips students with the knowledge and skills to conduct an independent scientific research project under the guidance of a lecturer. Students will be guided on research methods, from reading and synthesizing documents, analyzing and evaluating previous research works, developing new ideas, conducting experimental research (if any), writing scientific reports and presenting research results to the council. This course has a close relationship with all specialized courses that have been studied, applying and synthesizing the knowledge that has been equipped to solve a specific problem in the specialized field. The result of the course is a complete thesis and a demo program (if any), demonstrating the student’s ability to conduct independent and in-depth research.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Systematize learned knowledge and research a problem not yet in the curriculum.	CLO1: Understand scientific research methods or learn new technology.	PLO3-7
	CLO2: Understand the process of writing a graduate thesis.	PLO3-7
	CLO3: Deep understanding of a specific problem or new technology in the field of expertise.	PLO3-7
	CLO4: Build a demo program (if any).	PLO3-7
Skill
CO2: Practice self-study skills, search for documents, write reports, present problems.	CLO5: Search, read and synthesize scientific documents.	PLO9, 11
	CLO6: Analyze, evaluate and compare research projects or new technologies.	PLO9
	CLO7: Develop a research outline and conduct research. Write a report according to standards. Present and defend research results before a panel.	PLO10
Self-control and responsibility
CO3: proactive in work, adhere to research ethics.	CLO8: Proactive, creative and responsible in research.	PLO14
	CLO9: Have a spirit of cooperation and learning.	PLO13
	CLO10: Comply with scientific research ethics.	PLO15

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4
CLO2			4	4	4	4	4
CLO3			4	4	4	4	4
CLO4			4	4	4	4	4
CLO5									4		4
CLO6									4
CLO7										4
CLO8														4
CLO9													4
CLO10															4

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Due to the diverse nature of project topics, references will be updated and supplemented according to each specific topic. However, here are some general suggestions:

[1] Dawson, Catherine (2009). Introduction to research methods: a practical guide for anyone undertaking a research project . Howtobooks.

[2] Booth, W.C., Colomb, GG, & Williams, J.M. (2008). The craft of research . University of Chicago press.

[3] Scientific articles in specialized journals related to the topic.

[4] Published research works (theses, dissertations, theses).

[5] Faculty/school thesis writing guidelines.

Assessment of learning outcomes

Form and method of assessment

Assessment tools

Learning outcomes of the course

Weight

Product reviews, reports and protection

– Evaluate the quality of the thesis (content, form, scientific nature, novelty, applicability…).

– Evaluate students’ reporting quality, presentation skills and question answering skills

Rubric AM10c

CLO1-CLO10

100%

(Appendix – Assessment Rubric attached)

CS481V: Internship 1

General information about the course

Course name:				Course code: CS481V
Vietnamese Name: Internship 1 English Name: Internship 1
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major ☒ Graduation thesis/Project Supplement
Total credits: 04
Number of theoretical credits: 00	Number of practice credits: 00		Number of internship credits: 04
Number of theory periods: 00		Number of practice hours: 00
Number of practice hours: 180		Number of self-study hours: 180
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite courses *(if any)* : Consult with Academic Advisor or instructor.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	Dr. Truong Huu Tram	–	tram.truong-huu@ttu.edu.vn	Co-in charge
3	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	Co-in charge
4	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	Co-in charge
5	Assoc. Prof. Dr. Tran Vu Khanh	0989 282 522	khanh.tran@ttu.edu.vn	Co-in charge

Brief description of course content

Internship 1 is an important step in the training process, helping students apply the theoretical knowledge they have learned to the actual working environment of the enterprise. This course provides students with the opportunity to experience a professional working environment, be exposed to new technology and practice the skills necessary for their future career. The internship content is built on the coordination between lecturers and enterprises, ensuring practicality and conformity with the training program. This course has a close relationship with specialized courses. The work content is discussed and agreed upon by lecturers and enterprises. The minimum internship period is from 6 to 8 weeks.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: understand workflow, grasp technology in the business	CLO1: Apply acquired professional knowledge to practical work at the enterprise.	PLO3 – PLO7
	CLO2: Understand the business operations in the specialized field.	PLO3 – PLO7
	CLO3: Grasp new technologies, equipment and trends in the industry.	PLO3 – PLO7
Skill
CO2: time management, teamwork, corporate culture, problem presentation	CLO4: Practice teamwork, communication and presentation skills.	PLO10, 12
	CLO5: Develop problem solving and critical thinking skills. Enhance professional practice skills.	PLO8
Self-control and responsibility
CO3: self-discipline in work, business style.	CLO6: Be self-aware and proactive in assigned work. Develop a professional working style. Take responsibility for individual and group work results.	PLO13, 15
CO3: self-discipline in work, business style.	CLO7: Have the spirit of learning, progress and discipline.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4
CLO2			4	4	4	4	4
CLO3			4	4	4	4	4
CLO4										3		3
CLO5								4
CLO6													3		3
CLO7														3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

5.1. Documents on soft skills, report writing, presentation

[1] Stephen R. Covey, 1989, 7 Habits of Highly Effective People, Simon & Schuster. (Helps develop good habits in work and life)

[2] Dale Carnegie, 1936, How to Win Friends and Influence People , Simon & Schuster. (Focuses on communication skills, behavior and relationship building)

[3] Brian Tracy, Eat That Frog!, Berrett-Koehler Publishers. (On time management and prioritizing work)

[4] Some articles/videos/online courses on teamwork skills, presentation skills, problem solving skills, report writing skills. (Search on platforms such as Coursera, edX, YouTube…)

[5] Guidebook for writing scientific reports/internship reports (refer to the school library or search online).

[6] A guide on how to design effective presentation slides.

[7] Video tutorials on confident and engaging presentation skills.

5.2. Professional documents

[8] Books on programming (Java, Python, C++,…), network administration, database, network security,…

5.3. Guidance documents from businesses (very important) This is an extremely important group of documents and students need to pay special attention to. Including:

Company/enterprise introduction: Brochure, website, introductory slides, documents on history, organizational structure, fields of operation, corporate culture,…
Job Description: Details of the duties, responsibilities, authorities and requirements for the internship position.
Working process/SOP (Standard Operating Procedure): Instructions for specific work steps, regulations on labor safety, code of conduct,…
Report/evaluation form: Weekly/monthly work report form, internship evaluation form of the enterprise.
Technical documents/instructions: Internal company documents on technology, products, services, production processes, etc.
Contact information: Information of the direct instructor at the company and related departments.
Company regulations: Regulations on working hours, dress code, behavioral culture,…

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
1	Based on student internship reports, presentations and task performance.	Rubric AM10a (Part A)	CLO1-CLO7	30%
II	Business Reviews
1	Based on professional knowledge, practical skills, soft skills, work attitude, teamwork ability, work completion level, report quality.	Rubric AM10a (Part B)	CLO1-CLO7	70%

(Appendix – Assessment Rubric attached)

CS482V: Internship 2

General information about the course

Course name:				Course code: CS482V
Vietnamese Name: Internship 2 English Name: Internship 2
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major ☒ Graduation thesis/Project Supplement
Total credits: 06
Number of theoretical credits: 00	Number of practice credits: 00		Number of internship credits: 06
Number of theory periods: 00		Number of practice hours: 00
Number of practice hours: 270		Number of self-study hours: 270
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite courses *(if any)* : Consult with Academic Advisor or instructor.
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Cao Tien Dung	0983 695 166	dung.cao@ttu.edu.vn	In charge
2	Dr. Truong Huu Tram	–	tram.truong-huu@ttu.edu.vn	Co-in charge
3	Dr. Nguyen Xuan Ha	–	ha.nguyen@ttu.edu.vn	Co-in charge
4	Dr. Tran Duy Hien	0908 051 591	hien.tran@ttu.edu.vn	Co-in charge
5	Assoc. Prof. Dr. Tran Vu Khanh	0989 282 522	khanh.tran@ttu.edu.vn	Co-in charge

Brief description of course content

Internship 2 is an important stage that helps students apply the knowledge they have learned to the actual working environment at the enterprise. This course creates opportunities for students to continue to experience real work, get acquainted with corporate culture, develop professional skills and soft skills. Students will be assigned specific tasks under the guidance of lecturers and business instructors, and will be assessed on their knowledge, skills, attitudes and level of work completion. The course has a close relationship with specialized courses, helping students better understand the application of theoretical knowledge in practice. The content of the work is discussed and agreed upon by lecturers and businesses. The minimum internship period is from 10 to 12 weeks.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: understand workflow, grasp technology in the business	CLO1: Apply acquired professional knowledge to practical work at the enterprise.	PLO3 – 7
	CLO2: Understand the business operations in the specialized field.	PLO3 – 7
	CLO3: Grasp new technologies, equipment and trends in the industry.	PLO3 – 7
Skill
CO2: time management, teamwork, corporate culture, problem presentation	CLO4: Practice teamwork, communication and presentation skills.	PLO10, 12
	CLO5: Develop problem solving and critical thinking skills. Enhance professional practice skills.	PLO8
Self-control and responsibility
CO3: self-discipline in work, business style.	CLO6: Be self-aware and proactive in assigned work. Develop a professional working style. Take responsibility for individual and group work results.	PLO13, 15
CO3: self-discipline in work, business style.	CLO7: Have the spirit of learning, progress and discipline.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)	Learning outcomes of the program (PLO)
Course Output Standards (CLO)	PLO1	PLO2	PLO3	PLO4	PLO5	PLO6	PLO7	PLO8	PLO9	PLO10	PLO11	PLO12	PLO13	PLO14	PLO15
CLO1			4	4	4	4	4
CLO2			4	4	4	4	4
CLO3			4	4	4	4	4
CLO4										3		3
CLO5								4
CLO6													3		3
CLO7														3

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

5.1. Documents on soft skills, report writing, presentation

[1] Stephen R. Covey, 1989, 7 Habits of Highly Effective People, Simon & Schuster. (Helps develop good habits in work and life)

[2] Dale Carnegie, 1936, How to Win Friends and Influence People , Simon & Schuster. (Focuses on communication skills, behavior and relationship building)

[3] Brian Tracy, Eat That Frog!, Berrett-Koehler Publishers. (On time management and prioritizing work)

[4] Some articles/videos/online courses on teamwork skills, presentation skills, problem solving skills, report writing skills. (Search on platforms such as Coursera, edX, YouTube…)

[5] Guidebook for writing scientific reports/internship reports (refer to the school library or search online).

5.2. Professional documents

[6] Books on programming (Java, Python, C++,…), network administration, database, network security,…

5.3. Guidance documents from businesses (very important) This is an extremely important group of documents and students need to pay special attention to. Including:

Company/enterprise introduction: Brochure, website, introductory slides, documents on history, organizational structure, fields of operation, corporate culture,…
Job Description: Details of the duties, responsibilities, authorities and requirements for the internship position.
Working process/SOP (Standard Operating Procedure): Instructions for specific work steps, regulations on labor safety, code of conduct,…
Report/evaluation form: Weekly/monthly work report form, internship evaluation form of the enterprise.
Technical documents/instructions: Internal company documents on technology, products, services, production processes, etc.
Contact information: Information of the direct instructor at the company and related departments.
Company regulations: Regulations on working hours, dress code, behavioral culture,…

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Instructor Reviews
	Based on student internship reports, presentations and task performance.	Rubric AM10a (Part A)	CLO1-7	30%
II	Business Reviews
	Based on professional knowledge, practical skills, soft skills, work attitude, teamwork ability, work completion level, report quality.	Rubric AM10a (Part B)	CLO1-7	70%

(Appendix – Assessment Rubric attached)

MATH202V: General Mathematics 3

General information about the course

Course name:				Course code: MATH202V
Vietnamese Name: General Mathematics 3 English Name: Calculus 3
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : MATH201V (General Mathematics 2)
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	090 805 1591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

General Mathematics 3 course covers two basic topics in functions of many variables: multiple integrals and vector field calculus. These topics pave the way for future developments in advanced mathematics courses or applications in engineering and probability. The first part of the course is on double and triple integrals of functions of two or three variables. Students will learn how to use polar, cylindrical, and spherical coordinates in multiple integrals. The course introduces Fubini’s Theorem and changes of variables. The second part of the course focuses on vector field calculus. The main topics are line and surface integrals, which are connected to the double and triple integrals in the first part of the course by higher-dimensional versions of the Fundamental Theorems of Calculus that students encountered in Math 101: Green’s Theorem, Stokes’ Theorem, and the Divergence Theorem. The primary objective is to teach Chapters 15 and 16 of Stewart.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand and apply the concepts of multiple (double, triple) integrals and vector field calculus.	CLO1: Grasp the basic concepts of multiple integrals and vector field calculus and the relationship between differential and integral calculus of multivariable functions.	PLO1
CO2: Calculate multiple integrals, line integrals, surface integrals and apply Green’s, Stokes’, and divergence theorems to solve problems.	CLO2: Calculate multiple integrals of basic functions on different domains, calculate line integrals and surface integrals of certain surfaces and use Fubini’s Theorem, change of variables in multiple integrals, Green’s Theorem, Stokes’ Theorem and Divergence Theorem.	PLO1
	CLO3: Solve applied problems related to multiple integrals and vector field calculations (for example: calculating area, volume, work, flow)	PLO1
Skill
CO3: Logical thinking and problem solving skills.	CLO4: Analyze and interpret complex mathematical problems and apply appropriate solution methods.	PLO8
CO3: Logical thinking and problem solving skills.	CLO5: Develop logical reasoning skills, critical thinking and the ability to recognize mathematical models from real-life situations.	PLO8
Self-control and responsibility
CO4: Self-motivated in studying, researching, working in groups and being responsible for learning outcomes.	CLO6: Actively research and study documents related to the subject.	PLO14
	CLO7: Attend all classes; complete assigned exercises fully and on time.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] James Stewart, (2012), Calculus (Early Transcendentals) . Brooks/Cole Publishing Co.

Reference

Are not

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Diligent and active in class.	Rubric AM1	CLO7	10%
2	– Homework (individual).	Rubric AM2a	CLO1-CLO7	10%
3	– Test: Essay.	According to the answer	CLO1-CLO7	20%
4	– Midterm test: Essay.	According to the answer	CLO1-CLO7	25%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1-CLO7	35%

(Appendix – Assessment Rubric attached)

STA301V: Bayesian Statistics

General information about the course

Course name:				Course code: STA301V
Vietnamese Name: Bayesian Statistics English Name: Bayesian Statistics
Courses: ☒ Compulsory Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations ☒ Major Thesis/Graduation Project Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : STA206V
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	090 805 1591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

Bayesian Statistics course introduces Bayesian analysis and statistical decision theory, the theory of decision making under uncertainty. It covers topics such as the formulation of decision problems and the quantification of their components, optimal decisions, Bayesian models, simulation-based approaches to Bayesian inference (including MCMC algorithms), and hierarchical modeling.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Master the theory of Bayesian models and applications.	CLO1: Construct inputs for a decision problem that includes potential actions, losses and gains, and quantify uncertainty.	PLO1,7a,7b
	CLO2: Develop Bayesian statistical models to quantify uncertainty and make inferences about unknown model parameters.	PLO1,7a,7b
	CLO3: Understand how statistical techniques can help make important decisions in some real-world situations.	PLO1,7a,7b
	CLO4: Use posterior distributions to make optimal decisions based on available information.	PLO1,7a,7b
	CLO5: Use simulation-based approaches to obtain Bayesian inference.	PLO3
Skill
CO2: Ability to work effectively in a team on projects.	CLO6: Present and defend project results clearly and convincingly.	PLO10
CO2: Ability to work effectively in a team on projects.	CLO7: Work effectively in a team to complete projects, assign tasks and coordinate well with team members.	PLO12
reliance and responsibility
CO3: Ability to self-study, learn and update new knowledge in the field of data analysis.	CLO8: Actively seek and synthesize information from different sources to solve problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

CLO7

CLO8

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Think Bayes: Bayesian Statistics in Python by Allen Downey, 2nd edition, O’Reilly Media, 2021.

Reference

[2] Bayesian Statistics: An introduction by Peter M. Lee, 4th edition, Wiley, 2012.

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Process assessment
1	– Homework (individual).	Rubric AM2a	CLO1-CLO6	15%
2	– Diligent and quick to practice.	Rubric AM1	CLO1-CLO7	15%
3	– Midterm test: Essay.	According to the answer	CLO1-CLO5	20%
III	Final assessment
	– Final group project.	Rubric AM8b	CLO1-CLO8	20%
	Final exam: Essay.	According to the answer	CLO1-CLO8	30%

(Appendix – Assessment Rubric attached)

STA302: Probability and Random Processes

General information about the course

Course name:				Course code: STA302
Vietnamese Name: Probability and random processes English Name: Probability and Stochastic Processes
Courses: Compulsory ☒ Elective
Belonging to knowledge or skills: Overview of industry foundations Industry foundations Major Thesis/Graduation Project ☒ Supplement
Total credits: 03
Number of theoretical credits: 03	Number of practice credits: 00		Number of internship credits: 00
Number of theory lessons: 45		Number of practice hours: 00
Number of practice hours: 00		Number of self-study hours: 90
Number of assessment/discussion periods: 00
Number of other activities: 00
Prerequisite *(if any)* : General Mathematics 2
Course management department *(if any)* :

Information about the instructor

TT	Academic title, degree, full name	Phone number	E-mail	Note
1	Dr. Tran Duy Hien	090 805 1591	hien.tran@ttu.edu.vn	In charge

Brief description of course content

The course Probability and Stochastic Processes equips students with basic knowledge and skills in the ideas of probability theory; conditional probability and conditional expectation; Markov chains in discrete time; Poisson processes; Markov processes in continuous time and an introduction to Brownian motion.

Course objectives and output standards

Objectives	Learning outcomes of the Course (CLOs)	Learning outcomes of the program (PLOs)
Knowledge
CO1: Understand and apply advanced knowledge of probability.	CLO1: Provides a comprehensive yet easy-to-understand foundation in basic probability theory.	PLO1, PLO7
	CLO2: Introduces basic ideas and tools in the theory of stochastic processes	PLO1, PLO7
	CLO3: Develop and analyze probabilistic models to recognize randomness in systems probabilistically.	PLO1, PLO7
Skill
CO2: Ability to work in a team.	CLO4: Identify types of problems that can be applied in practice.	PLO8
CO2: Ability to work in a team.	CLO5: Work effectively in groups to complete assignments, assign tasks and coordinate well with members.	PLO12
reliance and responsibility
CO3: Ability to self-study, learn and update new knowledge in the field of probability model analysis, as well as a sense of responsibility.	CLO6: Actively search and synthesize information from different sources to solve problems.	PLO14

* Matrix of the contribution level of course output standards (CLO) to training program output standards (PLO)

Course Output Standards (CLO)

Learning outcomes of the program (PLO)

PLO1

PLO2

PLO3

PLO4

PLO5

PLO6

PLO7

PLO8

PLO9

PLO10

PLO11

PLO12

PLO13

PLO14

PLO15

CLO1

CLO2

CLO3

CLO4

CLO5

CLO6

Note: Contribution level on a scale of 1 to 5 (Level 1: Little contribution; Level 5: Big contribution)

Documents used for the course

Obligatory

[1] Sheldon M. Ross (2014), Introduction to Probability Models. Academic Press .

Assessment of learning outcomes

TT	Form and method of assessment	Assessment tools	Learning outcomes of the course	Weight
I	Progress Assessment
1	– Attendance and homework (group) in class.	Rubric AM1	CLO 6	10%
2	– Homework.	Rubric AM2a	CLO1-CLO6	20%
3	– Midterm test: Essay.	According to the answer	CLO1, 2, 3, 4	30%
II	Final assessment (end of term)
1	Final exam: Essay.	According to the answer	CLO1, 2, 3, 4	40%

(Appendix – Assessment Rubric attached)

List of the courses of the Computer science curriculum program 2022 (Teaching in Vietnamese)

LIST OF THE COURSES

OF THE COMPUTER SCIENCE

CURRICULUM PROGRAM 2022

(TEACHING IN VIETNAMESE)

HIS101V: History of world civilization

HIS102V: Modern Times

HUM101V: Essay Writing and Ideas

ENGL108: Introduction to Cultural Studies

ART101: Contemporary Art

CUL101: Vietnamese culture and some typical world cultures

HUM102V: Culture and Literature

MGT102: Leadership and Communication

HUM205: Language and Vietnamese

ENV101: People and the Environment

ENV102: Climate Change

ENTR101: Creative Entrepreneurship

PRFN01: Personal financial management

MACL108: Marxist-Leninist Philosophy

MACL109: Marxist-Leninist Political Economy

MACL104: Ho Chi Minh Thought

MACL110: Scientific Socialism

MACL111: History of the Communist Party of Vietnam

LAW102: General Law

INF102: Introduction to Computer Science

MACL1051: Physical Education 1

MACL1052: Physical Education 2

MACL1053: Physical Education 3

ESL101: English 1

ESLi101: Intensive English 1

ESL102: English 2

ESLi102: Intensive English 2

ESL103: English 3

ESLi103: Intensive English 3

ESL104: English 4

ESLi104: Intensive English 4

MATH101V: General Mathematics 1

DSP101: Introduction to Data Science with Python

EGD101: Engineering Design

MATH201V: General Mathematics 2

MATH110V: Linear Algebra

PHYS101V: Introduction to Mechanics

PHYS110V: Introduction to Electricity and Magnetism

CS111V: Introduction to Computer Science and Python Programming

STA206V: Statistical Probability

CS201V: Data Structures and Algorithms

CS202V: Discrete Mathematics for Computer Science

CS203V: Organization of Computers

CS204V: Algorithm Design and Analysis

CS205V: Operating System

CS206V: Object Oriented Programming

CS301V: Software Design and Implementation

CS302V: Web Application Development

CS303V: Mobile Application Development

CS304V: IoT Application Development

CS305V: Cloud Computing

CS311V: Introduction to Databases

CS330V: Introduction to Artificial Intelligence

CS331V: Introduction to Data Mining

CS332V: Introduction to Machine Learning

CS333V: Introduction to Computer Vision

CS334V: Natural Language Processing

CS364V: Application Security and Encryption

CS401V: Distributed Systems

CS408V: Software Project

CS411V: Big Data

CS412V: Information Extraction and Web Searching

CS413V: Data Processing

CS414V: Data Science Project and Implementation

CS431: Advanced Machine Learning

CS434V: Deep Learning

CS435V: Deep Learning Practice in Natural Language Processing

CS436V: Deep Learning Practice in Computer Vision

CS437V: Pattern Recognition

CS440V: Computer Networks

CS441V: Data Visualization

CS447V: Reinforcement Learning

CS450V: Topics in Data Science

CS470V: Graduation Project

CS471V: Graduation Essay