Curriculum
Programme Structure
Courses in the programme are categorized into Core Courses and Elective Courses. To obtain the award of Master of Science in Artificial Intelligence, students are required to take
- all 10 credits of the Core Courses, AND
- at least 21 credits of the Elective Courses.
Some of the Elective Courses are also designated as Stream Courses of the Autonomous Driving (AD) Stream, Generative AI (GAI) Stream or Trustworthy AI (TAI) Stream. Students may choose to:
- concentrate on a stream by taking 12 credits from the stream, comprising 2 stream core courses and 1 stream elective (either the Project or Internship course of that stream), and no more than 3 credits of courses from each of the other streams, OR
- take any Elective Courses without concentration on any stream.
Curriculum
Core Courses (10 credits)
| Code Code | Course Title | Credit Units | Remarks |
|---|---|---|---|
| CS5491 | Artificial Intelligence | 3 | |
| CS5486 | Intelligent Systems | 3 | |
| CS5489 | Machine Learning: Algorithms and Applications | 3 | |
| CS5611 | Seminar on AI Ethics | 1 |
Elective Courses (21 credits)
Group I Electives
| Code Code | Course Title | Credit Units | Remarks |
|---|---|---|---|
| CS5493 | Topics in Autonomous Driving | 3 | AD Stream Core |
| SDSC6007 | Dynamic Programming and Reinforcement Learning | 3 | AD Stream Core |
| CS6522 | Project in Autonomous Driving | 6 | AD Stream Elective |
| CS6523 | Internship in Autonomous Driving | 6 | AD Stream Elective |
| CS6493 | Natural Language Processing | 3 | GenAI Stream Core |
| CS5494 | Topics in Generative AI | 3 | GenAI Stream Core |
| CS6524 | Project in Generative AI | 6 | GenAI Stream Elective |
| CS6525 | Internship in Generative AI | 6 | GenAI Stream Elective |
| CS5495 | Explainable AI | 3 | TAI Stream Core |
| CS5297 | Topics in AI Security | 3 | TAI Stream Core |
| CS6526 | Project in Trustworthy AI | 6 | TAI Stream Elective |
| CS6527 | Internship in Trustworthy AI | 6 | TAI Stream Elective |
| CS6528 | Internship in Artificial Intelligence | 6 | |
| CS6529 | Project in Artificial Intelligence | 6 |
Group II Electives
| Code Code | Course Title | Credit Units | Remarks |
|---|---|---|---|
| CS5187 | Vision and Image | 3 | |
| CS5487 | Machine Learning: Principles and Practice | 3 | |
| CS6187 | Vision and Language | 3 | |
| CS6487 | Topics in Machine Learning | 3 | |
| CS6535 | Guided Study in Artificial Intelligence | 3 | |
| CS6491 | Topics in Optimization and its Applications in Computer Science | 3 |
More information:
- All the Project and Internship courses are mutually exclusive.
- Students must take 12 credits before taking a Project course.
- Students may only take the Internship course in their 2nd year of study, and after completing at least 22 credits.
- Students may only take up to 2 courses in Group II electives.
- Not all courses in the curriculum will be offered in every semester/term. The courses offered in each semester may vary depending on student demand, staff availability, and other circumstances.
Study Plans
Each student should plan his/her own study schedule to earn credits for the MSc in Artificial Intelligence award. Below are some sample study plans.
Please refer to Taught Postgraduate Catalogue for more information of individual courses.