Computer Science

General education knowledge: 50 CREDITS

Course	Credits
1. Marxist - Leninist Philosophy	3
Marxist - Leninist Philosophy module provides students with the most general knowledge of development and movement as a scientific basis for evaluating and solving problems arising in life. The module includes the basic contents: dialectical materialism, materialistic dialectism and historical materialism. Dialectic materialism provides learners with a scientific worldview as the basis for a positive and creative attitude to life. Dialectic materialism provides learners with a method of dialectic thinking to correctly recognize and solve problems in life. Historical materialism provides learners with a correct understanding of the existence and social development as well as the scientific methodology to recognize and solve social problems.
2. Marxist - Leninist Political Economics	2
The Marxist - Leninist Political Economy course is used for non-specialized political theory, studying the basic principles of Marxism-Leninism about the production of goods, the market and the role of actors in the economy. market economy. Research produces surplus value in a market economy, associated with it is the problem of capital accumulation and reproduction, along with manifestations of surplus value. The subject also studies competition and monopoly in the market economy. Study of the socialist-oriented market economy and economic interest relations in Vietnam. Study the strategy of industrialization, modernization and international economic integration of Vietnam.
3. Scientific Socialism	2
It is one of three constituent parts of Marxism-Leninism, a compulsory subject in the training program of universities and colleges in the country. The scientific socialism subject (social science) for the undergraduate degree without majoring in political theory equips students with the core content of the following specific issues: The process of formation and development of socialism; Working-class history mission; Socialism and the transition to socialism; Socialist democracy and a socialist state; The social-class structure and class alliances, class in the period of transition to socialism; Ethnic and religious issues in the transition to socialism; The family problem in the transition to socialism. On that basis, it helps students form their thinking, analytical skills, evaluate and identify the nature of socialism and the transition period to socialism in Vietnam, forming a school, Marxist-Leninist ideology, building appropriate social responsibility in employment and post-graduate life.
4. Ho Chi Minh’s Ideology	2
The Ho Chi Minh Thought module consists of 6 chapters, providing students with basic knowledge of: Objects, research methods, meaning of learning subjects. ; on the basis, process of formation and development of Ho Chi Minh's thought; Ho Chi Minh's basic ideas about national independence and socialism, the Communist Party of Vietnam, about national solidarity and international solidarity, culture, morality and people.
5. History of Vietnamese Communist Party	2
Equip students with the knowledge of objects, purposes, tasks, research methods, study of Party History and the basic, core, systematic knowledge about the birth of the Party (1920 - 1930), the process of the Party leading the struggle for power (1930 - 1945), leading two resistance wars against French colonialism and the American imperialist invasion, completing national liberation, reunification (1945) - 1975), led the country transitionally to socialism and carried out the reform (1975 - 2018). Thereby affirming the successes, raising the limitations, summarizing the experiences of the revolutionary leadership of the Party to help learners raise awareness, belief in the Party and the ability to apply the learned knowledge. into practical work, contributing to building and defending the Socialist Vietnam Fatherland.
6. Information Technology Law	3
This subject equips students of Computer Science, Information Technology, and Management Information Systems at UEH with the necessary legal knowledge to operate in a business environment related to information technology in Vietnam. Vietnam, focusing on comparison with advanced countries. The course consists of two parts: Part I Legal system of Vietnam. This section focuses on teaching learners to have a basic general understanding of the law, including: the origin of the law, the concept, the characteristics of the law and the regulatory mechanism of the law. From there, helping learners understand the nature and role of law in life, and have a respectful attitude towards the law. Part II Law in the field of information technology. This section equips students with basic knowledge about the legal system governing the behavior of subjects in the field of information technology. The main contents of this section include: intellectual property in the field of information technology, law on information technology enterprises, law on digital data and digital data protection, law on contracts. and dispute resolution in the field of information technology.
7. Microeconomics	3
Principles of microeconomics is an introductory course for students of Economics - Business and Management majors, teaching about the basic principles of microeconomics. This course will help us make decisions and understand how the world works by studying the behavior of economic actors in the market toward making decisions about allocating scarce resources. The subject focuses on the motives, how actors make decisions, and the interactions that affect other actors as well as the economy as a whole. The course also addresses market failures, which underlie government regulatory measures for optimal efficiency under competitive general equilibrium.
8. Macroeconomics	3
Macroeconomics studies the economy at the aggregate level, including: Describe and measure macroeconomic variables including output (GDP, GNI, GNDI), inflation, employment and unemployment. Apply simple macroeconomic models to explain the relationships between macroeconomic variables, for example those between government budget and economic growth and inflation, those between money supply and interest rate and exchange rate. Analyze short-run macroeconomic fluctuations, issues of business cycles, supply and demand shocks, the roles of fiscal and monetary policies in stabilizing the economy.
9. Management	3
This course will introduce students to general management principles and theories and complements students with basic knowledge and skills so that students would become knowledgeable employees or an efficient member of a team and a successful manager. This course will provide knowledge and skills appropriate to all economics and business students regardless of majors or individual career planning. In this course, we emphasize a combination of theory and practice. Students will be guided on how employees and managers of an organization can use theories and management principles to develop as individuals, excel in their work, and understand their organization. Many of the concepts and principles that would be taught in this course are very useful for the student's life as well as the students’ workplace. Those will help students improve their cognitive and behavioral skills to quickly achieve their career goals in an increasingly dynamic, diverse, and competitive business environment of the 21st-century.
10. Soft Skills	2
Soft skills course generates the foundation knowledge of soft skills, applicable to the workplace environment. The goal of learning is to combine the major knowledge with content and implementation of core soft skills techniques, giving students more effective access to the work environment after graduation. The core soft skills include Critical thinking; Problem-solving skills; Adaptability to the working environment; Effective communication and presentation skills; Service Oriented, Self-positioning skills, Feedback and Coaching.
11. Entrepreneurship	1
The course will build on cross-curricular academic skills, by integrating inquiry-based learning and business tools that will enable students to analyze, create, develop and pilot small businesses. Concepts and skills are reinforced by a strong emphasis on hands-on experiences. Applications to society, individuals, and the utilization of technology are included.
12. Introduction to Psychology	2
The objective of the field of psychology is to understand how the mind and brain interact with the external world to shape behavior. This course is designed to be an introduction to the science of psychology, which focuses mainly on the study of mind, emotion and behavior in humans. The course will provide basic knowledge that helps students build foundations in psychology. Furthermore, students will also understand how the knowledge of psychology is applied in management, economics, marketing, consumer behavior, technology management, and other fields. The contents of this course will include 3 modules: (1) Module 1: Introduction to psychology, (2) Module 2: psychological processes and behaviors, (3) Module 3: Correcting individual and social behaviors.
13. Sustainable Development	2
The course "Sustainable Development" introduces students to the key principles, concepts, and challenges of sustainable development with a focus on the context of Vietnam. As a rapidly developing nation, Vietnam faces complex social, economic, and environmental issues that require sustainable solutions. This undergraduate-level course aims to equip students with a comprehensive understanding of sustainable development theory, its application, and the role of various stakeholders in achieving sustainable outcomes. Studying "Sustainable Development" is essential for students to develop a holistic understanding of the challenges facing the world and to equip themselves with the knowledge and skills needed to contribute positively to a sustainable and equitable future. The course fosters critical thinking, global awareness, and responsible citizenship while providing a pathway to meaningful and impactful careers in a world that increasingly values sustainability.
14. Design Thinking	2
Design thinking is a problem-solving method that puts the user at the center of the process. It provides a dynamic framework for approaching idea formation, creative exploration, and divergent thinking. The Design Thinking course provides knowledge of principles, tools, and methods that promote creative thinking, such as Empathy Map, Persona/ User profile, Journey Mapping, How might we …?, Value Chain Analysis, Brainstorming, Mind Mapping, Story Telling, Problem Statement, Concept Development, Assumption Testing, Rapid Prototyping, Customer Co-Creation, Prototype to test, Experience Testing, Learning Launch….. Students will learn purposeful use of tools and alignment with process to solve real-world situations. They will develop skills in teamwork, critical thinking, presenting and expressing ideas. Students will learn how to communicate effectively, give and receive feedback, respect the ideas and perspectives of others.
15. General Business English	4
General Business English helps students: - Develop English language skills on the topics and contexts of work and business environments. - Have general knowledge of many fields such as careers, companies, selling, great ideas and stress. - Equip knowledge and skills to take the test for the international certificate of business communication English (TOEIC), contributing to achieving English output standards at level B1 (according to the European Framework of Reference, CFER).
16. English for Technology, Communication and Design 1	3
This module aims to enhance students' comprehension of academic language and literacy practices within the field of Technology, Communication and Design. The design of the module facilitates the integration of language learning with key content areas, enabling students to develop a profound understanding of how language functions in communicating subject matter. Consequently, students will be able to acquire essential language skills relevant to the field of Technology, Communication and Design. Students actively foster their learning experience through engaging in diverse learning activities such as case studies, role-plays, simulations, presentations, and group discussions.
17. English for Technology, Communication and Design 2	3
The principal aim of this module is to enhance students' cognitive mastery of the intricate interplay between academic language and the specialized discourse conventions within the field of Technology, Communication and Design. The structural framework of the module strategically facilitates the integration of linguistic acquisition with the foundational subject matter, thereby endowing students with the capacity to cultivate a profound comprehension of the nuanced role of language in the dissemination of specialized knowledge. Consequently, students will acquire and develop essential language competencies that are intrinsically pertinent to the field of Technology, Communication and Design. Students will be involved in various interesting activities like studying real cases, acting out scenarios, doing simulations, giving presentations, and having group discussions to make their learning experience exciting and valuable.
18. Mathematics for Computing	3
This module introduces basic ideas and methods in discrete mathematics, as well as essential mathematical tools in IT. The course illustrates the importance of discrete math concepts and provides relevant problem-solving tools for IT professionals, with a particular focus on problem solving using mathematical methods.
19. Fundamentals of Programming	3
This course equips the basics of programming techniques as one of the foundations in the fields of Computer Science and Information Technology. In addition, the course presents the basic concepts of algorithms and how algorithms are developed. The course also provides knowledge of C # programming languages such as: data types; declare variables, constants, expressions; assignment commands; import and export data; branch, loop control structures; 1 and 2 dimensional arrays; function / method; string type; file... so that students can apply the settings of the algorithms from elementary to advanced.
20. IT Research Methodology	2
The module equips students with basic knowledge about the process of conducting a scientific research project: identifying research topics, designing research, conducting research, and presenting research results. Students are also provided with the knowledge and skills necessary to conduct a practical research. In addition, students are introduced to tools to support report writing, citation, publication process as well as issues related to research ethics.

Subjects of Major: 12 CREDITS

Course	Credits
21. Computer Architecture and Operating Systems	3
The course provides learners with basic / basic knowledge of computer architecture and operating systems, helping learners to have foundational knowledge in the field of information technology. The course consists of two blocks of knowledge: Part 1: Computer architecture: system clusters, storage devices, I/O devices, communications and networks, system operations and performance enhancement. Part 2: Knowledge of Computer Operating Systems
22. Database	3
This module gives students the knowledge about data management; data exploitation; analyzing and designing data systems in information systems. From the above knowledge, students can build the data management and exploitation, according to the real needs of organization or business.
23. Data Structures and Algorithms	3
This course helps students understand the importance of organizing data and algorithms. The content of the course presents data structures including arrays, lists, stacks, queues, linked lists, trees, graphs; and today's popular search and sorting algorithms. In addition, the course also helps students supplement and perfect programming skills and programming thinking in building a computer program.
24. Computer Network	3
The course provides learners with basic knowledge about computer networks and the Internet. In addition, students understand how components in the computer network operate such as layers in the OSI model, basic protocols, ... In addition, students have access to learn and practice management. server on Windows Server operating system.

Subjects of Minor: 48 CREDITS

Course	Credits
25. Object-oriented Programming	3
This course introduces an object-oriented approach to programming, demonstrates the importance of object-oriented programming and its advantages over structured programming. The main contents provided include: concepts and principles of object oriented programming; how the class and its components are designed; implements object-oriented properties such as inheritance, closure, abstraction, polymorphism. Through practicing some simple applications on the C# programming language to gain insight into the key properties of the object-oriented model.
26. Theory of Graph	3
The module aims to equip students with basic mathematical knowledge of graphs and trees. In addition, the module will help students practice programming skills to install algorithms on graphs and trees such as finding directions, finding maximum trees and coloring maps. The knowledge and skills gained from this module will be the foundation to help students later be able to solve some problems applied in practice.
27. Python Programming	3
The module aims to equip students with the basics of the Python language. In addition, the module will help students practice programming skills in Python language such as control structures, data structures that gather and handle common file types. The knowledge and skills gained from this module will be the foundation for students to later be able to install algorithms or analyze data from basic to advanced.
28. Artificial Intelligence	3
This course aims to equip learners with basic knowledge of the problem-solving methods of Artificial Intelligence (AI), skills of applying AI methods to practical problems of the socio-economic field. On that basis, it helps learners with necessary knowledge and skills to participate in the development of software projects for research and management in the fields of marketing, supply chain management, and financial analysis. Credit performance analysis.
29. Machine Learning	3
This course aims to equip learners with the basics of machine learning (ML) methods, as well as practice the application of ML to practical socio-economic problems. On that basis, it helps learners have the necessary knowledge and skills in data analysis using ML, can participate in research projects in the fields of marketing, supply chain management, analysis. Finance, credit activity analysis.
30. Data Mining	3
This course equips students with the basics of data mining. Also provide students with algorithms for data mining through the use of computers. From that knowledge, students can apply to program or use libraries to make functions for consulting or decision-making purposes.
31. Introduction to Formal Languages	3
Formal languages are used in the construction of programming languages, the theory of translated programs. Formal languages form a descriptive engine for computational models both for input-output and for manipulation. Formal language theory, precisely because it is an interdisciplinary field of science; The need to describe grammatical form has arisen in many sciences ranging from formal linguistic theory to biology. The pertinent aspects of formal language theory will therefore be of decisive importance in the textbooks of Formal Language Theory and automatism. The course provides basic knowledge about Formal Languages and abstract machines (automats, grammars, turing machines). This is a must-have for students of computer science. On that basis, students can gain a deeper understanding of the structure of programming languages, translation programs as well as the nature of algorithms and their computational complexity.
32. Cloud Computing	3
This course introduces the knowledge and skills necessary for students to have a clear understanding of cloud computing and the technology trends related to cloud computing today. In addition, students will be given discussion topics / exercises to apply knowledge learned.
33. Functional Programming	3
Functional programming is one of the basic programming subjects that equips students to program based on pure functions like mathematical functions. The course helps students apply mathematical knowledge to programming to prove that a program does its job correctly or to find simpler, easier to understand solutions to problems. Students will be equipped with functional programming skills through popular languages such as Haskell or javascript.
34. System Programming	3
The course content focuses on how applications are created by combining small programs and exchanging them over pipes, files, mass memory, or networks. The course also equips multi-threaded and shared-memory programming skills on the basis of the NUMA computer architecture (a modern computer model with a single processor or multiple cores). Students will be equipped with knowledge of parallel programming, using different levels of caching, locking and synchronization types.
- Elective: Select 1 out of 2	3

35. Stochastic Process	3
This course is designed to provide students with a foundational understanding of stochastic processes as they apply to the economics and finance. Topics will include an introduction to stochastic processes, Markov processes, Martingales, Brownian motion, Stochastic calculus and stochastic differential equations.
36. Introduction to Acoustic Processing	3
The module provides students with knowledge of audio and voice signals, sound and voice processing techniques such as coding techniques, sound smoothing, etc. In addition, the above audio and voice processing skills are based on software solutions that will help students apply to practical problems such as noise separation, sound smoothing, or advanced processing problems such as text-to-speech. In addition, students are also acquainted with dedicated audio and voice processing libraries for future work.
- Elective: Select 1 out of 2	3

37. Game Theory	3
The course provides a framework used to study strategic interactions between participants through their decision making. After completing this module, students will be able to (i) Explain some economic phenomena such as competitiveness, quality of labor force, salary level, impact of policies; (i) Modeling a decision problem, using game theory concepts and from the assumptions of the particular problem; and (iii) Use tools to solve them based on the principles learned. The main content is related to the goal of the game (solution concept), in which the Nash equilibrium plays an important role, depending on the form (static, dynamic, normal, extended, Bayesian) and information (complete, not enough). Thereby examining specific economic models such as oligopoly, job market signals, adverse selection, bargaining, auctions, and efficient wages.
38. Image Processing & Analysis	3
The module provides basic knowledge about digital images, digital image processing methods and algorithms, digital image analysis and machine vision technologies related to object recognition. In addition, skills related to applying methods of image recovery, separation, image quality enhancement, image segmentation to serve other post-processing operations in machine vision also help students solve practical problems related to digital images. In addition, the module also provides students with the skills to use software libraries to support image processing and analysis techniques.
- Elective: Select 1 out of 3	3

39. Natural Language Processing	3
Equip students with basic knowledge of computational linguistics and specialized knowledge of natural language processing. At the same time, provide students with libraries that support natural language processing.
40. Operation Research	3
Operations learning aims to introduce students to common mathematical models used in decision-making problems. A variety of deterministic models such as: nonlinear programming models, linear programming models, network programming models, integer programming models are used to solve practical problems. In addition, the module also provides knowledge to help students convert practical problems into mathematical models of Operations Learning, from which they can apply the methods they have learned to solve. In addition, students learn how to analyze and represent results with the help of software solutions.
41. GUI Design	3
The course provides comprehensive knowledge of the technologies of user interface design and implementation. Topics include the foundation of human-computer interaction, methods of building graphical user interfaces, interactive devices and technologies, cognitive models, usability, and processes. design and development, user interface management systems, interface design techniques and styles
- Elective: Select 1 out of 2	3

42. Decision Support Systems	3
This module provides students with knowledge about management support, decision-making and decision support. At the same time, it provides students with an understanding and analysis of the components, models, and algorithms of decision support systems. Finally, the course gives students the skills to orient the development of decision support. Contents include: - Overview of management support - Decision-making model and system - Decision support system - Introduction to the data management branch in decision support - Introduction to the model branch in decision support - Introduction to the branch of knowledge management in decision support - Decision support system development process
43. Computer Graphics	3
The module aims to equip students with basic knowledge of computer graphics, algorithms for drawing shapes, coloring, lighting, shading, reflections, etc. Students will also learn basic techniques for creating movement. In addition, students are also equipped with the necessary skills to implement algorithms based on the popular graphics library, OpenGL.
- Elective: Select 1 out of 2	3

44. Introduction to Deep Learning	3
Deep Learning is an area of artificial intelligence (AI) that involves building deep neural network models to solve complex problems, such as image classification, automated translation, and data analysis. Deep Learning is a deep neural network-based machine learning method in which layers of neurons link together to learn from input data and generate predictions for new data. Deep Learning is a rapidly growing field and has many applications in fields ranging from healthcare to industrial automation. It is considered one of the important trends in artificial intelligence today. Deep Learning focuses on how to build and train deep neural network models, along with techniques to optimize these models. Deep Learning courses also cover solving complex problems using deep neural network models, including applications in image processing, natural language, and robot control. Deep learning also often delves into the core techniques of machine learning, including optimizing and calibrating models, processing missing data, and minimizing overfitting. Some common tools used in deep learning include TensorFlow, Keras, and PyTorch. The course content consists of four parts Chapter 1: Introduction to Deep Learning Chapter 2: Neural Networks Basics Chapter 3: Convolutional Neural Networks Chapter 4: Recurrent Neural Networks Chapter 5: Deep Learning for Computer Vision Chapter 6: Natural Language Processing with Deep Learning. Chapter 7: Deep Reinforcement Learning
45. Computational Economics	3
The course equips computational methods used to solve basic problems in Economics. The calculation methods include: matrix method, optimal method, integral method, probability method and optimal control method. After completing the module, students have the ability to analyze Economic problems to choose a method to solve and represent problems suitable for this method, and use software tools to solve and present results.
- Elective: Select 1 out of 3	3

46. Analytics of Social Network Data	3
This course focuses on harnessing data from social networks such as Twitter, Facebook, LinkedIn, Google+, and GitHub. Students will learn how to use open source tools to retrieve data, process data, and visualize collected data. The course content consists of five parts •Chapter 1: Overview of data mining from social networks: In this chapter, students will be introduced to the basic concepts of data mining from social networks, including the applications and challenges of the field. Chapter 2: Using APIs to Get Data from Twitter, Facebook, and LinkedIn: This chapter focuses on how to use Twitter, Facebook, and LinkedIn APIs to get data. Students will learn how to make API requests, handle returned data formats, and create computer programs to retrieve data. •Chapter 3: Processing and Analyzing Collected Data: In this chapter, students will learn how to use Python tools to process data collected from social networks. These tools include the pandas library for processing data in the form of tables and the matplotlib library for data visualization. •Chapter 4: Data visualization with charts and graphs: In this chapter, students will learn how to use Python tools to visualize data collected from social networks using charts and graphs. These tools include the seaborn library for drawing statistical graphs and the network library for plotting link graphs. •Chapter 5: Application of Data Mining Techniques: This chapter focuses on data mining techniques to find information and detect connections from data collected from social networks. Students will learn how to use these techniques to analyze data and find specific information, for example searching for popular hashtags on Twitter or searching for similar user groups on LinkedIn. All chapters in the course use the Python programming language and popular libraries such as pandas, matplotlib, seaborn, network, and other software development tools.
47. Expert Systems	3
This module provides students with specialist knowledge. At the same time, it provides students with an understanding and analysis of the components, models, and algorithms of decision support systems. Finally, the course gives students developmental orientation skills and builds decision support. Contents include: - Expert system overview - Structure of the expert system - Expression of knowledge - Inference method - Fuzzy logic and fuzzy deductive systems - Introduction to PROLOG and CLIPS languages - Generation development
48. Multimedia Content Creation	5
The module provides basic knowledge related to multimedia content such as graphics, audio and video. To create diverse and engaging multimedia content, students need to have knowledge of specialized multimedia content creation software. In addition to learning about software solutions for multimedia design, students are also provided with knowledge related to the principles of designing multimedia content to achieve aesthetics and increase interactivity. In addition, students also interact in groups to promote critical thinking in the transmission of design content.

General education knowledge: 50 CREDITS

Subjects of Major: 12 CREDITS

Subjects of Minor: 48 CREDITS

Graduation Internship: 10 CREDITS

Total credits: 120 CREDITS

UEH Standard Programs

General education knowledge: 50 CREDITS

Subjects of Major: 12 CREDITS

Subjects of Minor: 48 CREDITS

Graduation Internship: 10 CREDITS

Total credits: 120 CREDITS