Data Science

Data Science is the science of collecting, processing, managing and analyzing data to discover the knowledge contained in data. The information that has been discovered plays an important role in making future decisions for action or strategic planning.

Introduction

Data is an extremely important source of information for companies and businesses to map out business strategies and development. In the current 4.0 era, data is increasing in a huge size. That creates a huge need for data storage and analysis as well as building computer-aided programs and algorithms.

In Vietnam, many large organizations have been researching and applying data science in an intensive and methodical way such as VinAI Institute, Viettel, FPT, VNG,... Therefore, experts in data science will have increasing demand and potential in the current 4.0 revolution.

Program code

7460108

Duration

4 years

Degree

Bachelor of Data Science

Subject combination

A00: Math – Physics – Chemistry

A01: Math – Physics – English

C01: Mathematics – Literature – Physics

D01: Math – Literature – English

Excellent features of the training program

The Data Science training program equips students with the most up-to-date knowledge and skills, building a learning environment so that students can develop their ability to work in an international environment after graduation.

Focus on international environmental working skills

The learning method focuses on practice and soft skills. The English program is taught exclusively to students from the first year to ensure good communication skills after graduation and working in a

Update new knowledge in the world

Students are given accounts to take Coursera, Udacity, Udemy live courses,...

Interactive learning environment

The faculty holds regular and rotating academic seminars throughout the academic period. Sharing from guests who are leading experts in the field of Data Science and Artificial Intelligence is an oppo

Program learning outcomes

With a 4-year structure design, the bachelor's program in Data Science aims to equip students with the necessary competencies to thrive in an international environment.

Mastering technical expertise

Proficient in techniques to solve problems in the data science industry.

Project management capabilities

Manage projects related to the field of software and data science.

Capacity for autonomy and responsibility

Demonstrate work ethic, community responsibility, and participation in lifelong learning.

Adapt to change

Adapt to the changes of science and technology in the context of industrial revolution 4.0.

Ability to apply multi-knowledge

Apply knowledge of natural sciences, social sciences, human environment to solve problems related to the expertise of Data Science.

Application of statistics and data analysis platform

Apply general principles and core technical foundational elements in the field of statistics and data analysis to Data Science.

Offer industry-related solutions

Propose solutions to solve problems related to the Data Science industry.

Proactively solve problems

Ability to solve problems related to Data Science.

Scientific research

Participation in scientific research (document survey, analysis, evaluation) in the field of artificial intelligence.

Ability to think systems

Develop the ability to think systematically about components or entire systems of data collection and analysis.

Teamwork capabilities

Engage in effective teamwork as a team member or leader.

Ability to communicate and express

Communicate ideas through language, text, speech, etc. to solve problems in technical and non-technical environments.

Mastering technical expertise

Proficient in techniques to solve problems in the data science industry.

Project management capabilities

Manage projects related to the field of software and data science.

Capacity for autonomy and responsibility

Demonstrate work ethic, community responsibility, and participation in lifelong learning.

Adapt to change

Adapt to the changes of science and technology in the context of industrial revolution 4.0.

Ability to apply multi-knowledge

Apply knowledge of natural sciences, social sciences, human environment to solve problems related to the expertise of Data Science.

Application of statistics and data analysis platform

Apply general principles and core technical foundational elements in the field of statistics and data analysis to Data Science.

Offer industry-related solutions

Propose solutions to solve problems related to the Data Science industry.

Proactively solve problems

Ability to solve problems related to Data Science.

Scientific research

Participation in scientific research (document survey, analysis, evaluation) in the field of artificial intelligence.

Ability to think systems

Develop the ability to think systematically about components or entire systems of data collection and analysis.

Teamwork capabilities

Engage in effective teamwork as a team member or leader.

Ability to communicate and express

Communicate ideas through language, text, speech, etc. to solve problems in technical and non-technical environments.

Mastering technical expertise

Proficient in techniques to solve problems in the data science industry.

Project management capabilities

Manage projects related to the field of software and data science.

Capacity for autonomy and responsibility

Demonstrate work ethic, community responsibility, and participation in lifelong learning.

Adapt to change

Adapt to the changes of science and technology in the context of industrial revolution 4.0.

Study Program

The Data Science training program at Van Lang University is designed in a 4-year structure, with a total of 131 credits.

Data Science Major

1ST YEAR

2ND YEAR

3RD YEAR

4TH YEAR

English 1,2,3

Philosophy of Marxism - Leninism

Scientific Socialism

Marxist - Leninist Political Economy

Management

Introduction to Data Science

Soft Skills

Physical Education

Applied Informatics

Environment and Human

Mathematics for data science

Probability Theory and Mathematical Statistics

Data Science and Application Project 1

Our teaching, learning and evaluating methods

The Faculty applies various teaching methods including: lectures, situational illustrations, practice, extracurricular activities, focusing on technology for students to have the best learning experience.

Learning methods

Students actively prepare lessons, read syllabuses and reference materials before each session, attend full classes, do exercises under the guidance of the lecturer.

Teaching methods

Depending on the module, there will be different teaching methods. For theoretical modules, teaching methods combined with projection and writing are commonly applied. For practical modules, students will be instructed to do it on a computer.

Evaluation methods

Combine a variety of methods to ensure flexible and comprehensive assessments such as tests, large assignments, essays, and projects.

Career Prospects

After graduating from this training program, learners can work at the following organizations and enterprises:

Work in outsourcing companies or developing information technology products at home and abroad

Work in large companies or enterprises that need to process, analyze data, statistics and make decisions

Work in research institutes and technology transfer units in the field of data science

Lecturers teaching in universities, colleges, professional secondary schools

Ability to continue studying Master's and Doctoral training programs in Data Science, Computer Science

Geoffrey Moore, American Management Consultant and Author

"Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway."

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