Data Science and AI Engineering Program Overview

Data Science and AI Engineering Program Overview

Program Overview

The Data Science and AI major is designed to equip students with practical skills for a career in the rapidly growing and highly demanded field of Artificial Intelligence. The curriculum focuses on providing comprehensive knowledge and essential tools and technologies required in this era of Industrial Revolution 4.0, including machine learning, deep learning, natural language processing, computer vision, big data analysis, and other related sub-fields. Students will engage in project-based learning, gaining industry-level experience from their early years through collaborative teamwork and utilizing the latest industry tools and technologies. They will learn how to collect, analyze, and interpret large amounts of data using appropriate methods and technologies, and build predictive models and algorithms to solve real-world problems in various industries such as healthcare, finance, marketing, and more. In addition to the hand-on approach in the university, the one-year industry placement program will provide students with an opportunity to gain hands-on experience in a real-world work environment, helping them acquire practical knowledge and skills that can prepare them for a successful career. Graduates with an AI and Data Science degree can pursue careers as science researchers, data scientists, machine learning engineers, AI specialists, business analysts, and big data professionals. Their expertise allows them to design and develop intelligent algorithms and apply analytical methods to gain valuable insights for organizations. 

Program Learning Outcomes

  • Acquire deep understanding of the mathematical, statistical foundations, algorithms, problems solving, tools and technologies used in the data science and AI industries (knowledge)
  • Understand and apply machine learning, natural language processing, computer vision, data analysis and related sub-fields to solve real-world problems (Cognitive Skills)
  • Develop critical thinking and problem-solving skills to tackle complex data science and AI challenges (Cognitive Skills)
  • Apply ethical considerations in the development of AI systems, including issues related to bias, privacy, and data security (Interpersonal Skill and Responsibility)
  • Stay up-to-date with the latest advancements and trends in the field of data science and AI (Interpersonal Skill and Responsibility)
  • Develop effective team work and communication skills to present complex data science and AI concepts to both technical and non-technical audiences (Communication, Psychomotor Skills). 

Program Structure

The 4-year Bachelor’s Degree program contains 156 credits combining from 106 credits of coursework, 48 credits of internship and 2 credits of Industrial Placement Report. The courses are divided into three categories, including Common Courses, Specialized Courses, and Elective Courses.

Common courses 

ENG101: Core English

ENG102: Core English

ENG103: Academic Writing Skills 

RES101: Research Methods

PRO101: Computer Fundamentals

CHN101: Chinese

CHN102: Chinese

STA101: Statistics and Probability

SDE101: Social and Digital Entrepreneurship

PHI101: Philosophy and Anthropology of Technology 


9 internships (3 internships per term)

Specialised courses

MAT101: Applied Math

PHY101: Physics 

P001: Algorithms  

ISP201:Introduction to Software Engineering 

DSA202: Data Structure and Algorithms 

CA203: Computer Architecture 

DB204: Database

OOC205: Object Oriented Concept

AI206: Introduction to AI 

OSCN207: Operating System and Computer Network

SDS208: Software Design and Security

ICPS209: Introduction to Cyber-Physical Systems 

DSA321: Data Science and Application

ML322: Machine Learning 

BI323: Business Intelligence 

CV324: Computer Vision and Application  

CC325: Cloud Computing 

NLP326: Natural Language Processing  

BD327: Big data analytics 

EA328: Enterprise Applications

DEE329: Data Engineering Ethics

Elective courses

HUM101: Introduction to Humanities

GLO101: Global Studies 

ENV101: Environment and Geography 

PRO102: Object-Oriented Programming 

MAT101: Applied Math

ATR101: Fine Arts 

ARC101: Computer-Aided Design

PHY101: Physics

RES101: Research Methods

COM101: Computer Fundamentals

(other 6 elective courses from other faculties)

Job Prospects

  • Data Engineer 
  • Data Analyst
  • Business Intelligence Analyst
  • Machine Learning Engineer 
  • AI Specialist
  • Chief Technology Officer
  • Computer Vision engineer
  • Science Researcher