Data Science and AI Engineering Program Overview
December 6, 2023 2024-09-06 10:14Data 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
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 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
Internship
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