1. Program Introduction:
Industry 4.0 or the Fourth Industrial Revolution refers to interconnectivity, automation, and real-time data exchange. There is tremendous growth in big data from the Internet of things (IoT) and artificial intelligence (AI), extensive applications, and integrations of modern technological devices (smartphones or tablets). Big data can provide a lot of valuable insights. Therefore, if the data is collected, exploited, and analyzed, it would bring many great benefits to business, scientific research, forecasting natural disasters, epidemics, etc.
With the outstanding development of data science, more and more businesses in the fields of Science & Technology, Marketing, Banking & Finance, and Insurance have invested in this field.
Data science is known as a new profession and is highly demanded over the world in general and in Vietnam in particular. The Harvard Business Review states that “Data Science would be the Most Attractive Profession of the 21st Century”. In the U.S, Data Science has ranked in the Top 10 the most recruited occupations, Top 16th for the highest salary, and Top 25 for the best occupations. In Vietnam, the demand for qualified human resources for data science has rapidly increased.
The Bachelor Program in Data Science is built based on USTH’s strength in training in information technology, statistics, and big data analysis in the sciences and technologies. The program would meet the demand for qualified human resources in Industrial 4.0.
2. Program Curriculum:
Our program is divided into 3 years (6 semesters), as follows:
- The first year (60 credits) provides students with background knowledge in Science & Technology;
- The second-year (60 credits) focuses on the ICT and Applied Mathematics pathway, the major building blocks of Data Science;
- The third-year (60 credits) includes specialized and applied data science in science and technology disciplines such as Biotechnology, Environmental Science, Remote Sensing, and Applied Mathematics.
No | Course name | Group | ECTS |
Semester 1: 29 ECTS | |||
1 | English | Language | 8 |
2 | Management Sciences | MS | 2 |
3 | Linear Algebra | MATHS | 4 |
4 | Introduction to informatics | ICT | 3 |
5 | Fundamental Physics I | PHYSICS | 4 |
6 | Cellular biology | BIOLOGY | 4 |
7 | General Chemistry I | CHEMISTRY | 4 |
Semester 2: 31 ECTS | |||
1 | Basic programming | ICT | 4 |
2 | Calculus I | MATHS | 4 |
3 | Fundamental Physics II | PHYSICS | 4 |
4 | Genetics | BIOLOGY | 3 |
5 | General Chemistry II | CHEMISTRY | 4 |
6 | Introduction to Algorithms | ICT | 3 |
7 | Computer Architecture | ICT | 3 |
8 | Calculus II | MATHS | 3 |
9 | Discrete Mathematics | MATHS | 3 |
Semester 3: 32 ECTS | |||
1 | Management Sciences | MS | 2 |
2 | French | Language | 8 |
3 | Probability | MATHS | 3 |
4 | Numerical Methods | MATHS | 3 |
5 | Data Structures and Algorithms | ICT | 3 |
6 | Object-oriented Programming | ICT | 4 |
7 | Fundamentals of Databases | ICT | 3 |
8 | Machine Learning and Data Mining I | DS | 3 |
9 | Signal and Systems | ICT | 3 |
Semester 4: 28 ECTS | |||
1 | Advanced Programming | ICT | 4 |
2 | Algebraic Structures | MATHS | 3 |
3 | Statistics | MATHS | 3 |
4 | Introduction to Artificial Intelligence | DS | 3 |
5 | Image Processing | DS | 3 |
6 | Machine Learning and Data Mining II | DS | 3 |
7 | Software Engineering | ICT | 3 |
8 | Fundamentals of optimization | MATHS | 3 |
9 | Applied Statistics and Experimental Design | MATHS | 3 |
Semester 5: 30 ECTS | |||
1 | Management Sciences | MS | 2 |
2 | French | Language | 7 |
3 | Fundamentals of Data Science | DS | 3 |
4 | Advanced Databases | ICT | 3 |
5 | Distributed Systems | ICT | 3 |
6 | Computer Vision | DS | 3 |
7 | Data Visualization | DS | 3 |
8 | Web/Text Mining | DS | 3 |
9 | Introduction to BioInformatics | Applied DS | 3 |
Semester 6: 30 ECTS | |||
1 | Analysis of Spatial and Temporal Data | Applied DS | 3 |
2 | Natural Language Processing | Applied DS | 3 |
3 | Time Series Data and Analysis | Applied DS | 3 |
4 | Graph Analytics for Big Data | Applied DS | 3 |
5 | Machine Learning in Medicine | Applied DS | 3 |
6 | Group Project | DS | 3 |
7 | Internship | DS | 12 |
USTH’s students will be equipped with knowledge in data science such as data mining, machine learning, visualization, predictive modeling & statistics, analysis; statistics-oriented programming languages, and big data tools.
Being a skill-oriented pathway, we expect an evenly distributed teaching hour for each course: 50% for theory and 50% for practical work. In more “theory-oriented” courses, this ratio can be 70% lectures and 30% practical work. These proportions encourage students to really get into the field.
The program is fully taught in English including lectures, practical works, and tutorials. The international environment gives students great advantages when compared with traditional domestic programs, especially with the ability to self-study and research.
The full-time internship can be either at a company or at a laboratory. With existing collaborations between USTH’s partners and businesses, the students can easily find an intern position.
In addition, students will also be trained in professional working style, and logical thinking, and equipped with soft skills such as presentation, argument, teamwork, leadership skills, project proposal writing, and report writing to confidently adapt to the international environment upon graduation.
3. Career Opportunities:
Graduated students can apply to the following positions:
- Data Analyst
- Data Engineers
- Database Administrator
- Machine Learning Engineer
- Data Scientist
- Data Architect
- Statistician
- Business Analyst
- Data and Analytics Manager