Distribution of Curriculum
| Courses | Credits | Percent |
|---|---|---|
| General Courses | 39 | 30.23% |
| Core Courses | 27 | 20.93% |
| Major Courses | 47 | 36.44% |
| Internship, Thesis | 16 | 12.4% |
Program Summary
Learning Objective: Develop a strong foundation in managing, processing, and analyzing big data, encompassing both theoretical and applied aspects of data science within information systems. Enhance problem-solving skills for analyzing, optimizing, and designing information systems through extensive data analysis. Acquire the ability to design, develop, and integrate information systems for technical applications focused on comprehensive data analysis, with a capability to address interdisciplinary issues in engineering, social sciences, politics, and economics. Gain expertise in data science and information systems to thrive in a data-driven world.
Career Opportunities: A Bachelor of Data Science offers many career options, including roles as an analyst, designer, and developer of intelligent data mining software. Undergraduates can find opportunities in businesses, government agencies, research institutes, and leading software development companies like DXC, FPT, IBM, TMA, TPS, and Microsoft. Additionally, they can explore diverse fields related to data analysis, mining, and processing.
Module handbook: link
Curriculum
| Subject | Credits | Subject | Credits |
|---|---|---|---|
| Semester 1 | 15 | Semester 2 | 17 |
| Calculus 1 | 4 | Probability, Statistic & Random Process | 2 |
| Introduction to Data Science | 3 | Linear Algebra | 3 |
| Writing AE1 | 2 | Writing AE2 | 2 | Listening AE1 | 2 | Speaking AE2 | 2 |
| Fundamentals of Programming | 4 | Philosophy Marx -Lenin | 3 |
| Object-Oriented Programming | 4 | ||
| Semester 3 | 17 | Semester 4 | 20 |
| Marx-Lenin Political Economy | 2 | Scientific Socialism | 2 |
| Statistical Method | 3 | General law | 3 |
| Data Structures and Algorithms | 4 | Artificial Intelligence | 4 |
| Principles of Database Management | 4 | Statistical Learning | 4 |
| Fundamental Concepts of Data Security | 4 | Regression Analysis | 4 |
| Physical Training 1 | 3 | ||
| Semester 5 | 18 | Semester 6 | 18 |
| History of Vietnamese Communist Party | 2 | Ho Chi Minh’s Thoughts | 2 |
| Data Science and Data Visualization | 4 | Machine Learning | 4 |
| Data Mining | 4 | Deep Learning | 4 |
| Scalable and Distributed Computing | 4 | Elective | 4 |
| Data Analysis | 4 | Elective | 4 |
| Semester 7 | 17 | Semester 8 | 13 |
| Special Study of the Field | 3 | Internship | 3 |
| Big Data Analytics | 4 | Thesis | 10 |
| Physical Training 2 | 3 | ||
| Elective | 3/4 | ||
| Free Elective | 3/4 |
Elective Courses
The Elective course for all levels of English proficiency:
| Course | Credits |
|---|---|
| Business Process Analysis | 4 |
| Decision Support Systems | 4 |
| Theory of Networks | 4 |
| Time Series Analysis | 4 |
| Blockchain | 4 |
| Software Engineering | 4 |
| IT Project Management | 4 |
| Information System Management | 3 |
| Cloud Computing | 4 |
| Entrepreneurship | 3 |
| Natural Language Processing | 4 |
| Human-Computer Interaction | 4 |
| Optimization and applications | 4 |
| Web Application Development | 4 |
| Discrete Mathematics | 3 |