Programmes

Master of Science in Artificial Intelligence

Programme	Master of Science in Artificial Intelligence 理學碩士(人工智能)
Award Title	Master of Science in Artificial Intelligence 理學碩士(人工智能)
Offering Academic Unit	Department of Computer Science
Mode of Study	Combined mode

Normal Period of Study

- 1 year (Full-time)
- 2 years (Full-time with year-long internship/project course)
- 2 years (Part-time/Combined mode)

Maximum Period of Study

- 2.5 years (Full-time)
- 3 years (Full-time with year-long internship/project course)
- 5 years (Part-time/Combined mode)

Credit Units Required for Graduation

Programme Aims

The programme aims to (1) equip information technology professionals with enhanced technical capabilities in Artificial Intelligence, (2) broaden students’ knowledge and deepen their understanding of specific areas in Artificial Intelligence from both the technical and practical perspectives, and (3) prepare graduates to take up research and advanced innovative development work in the industry or pursue higher research studies in Artificial Intelligence.

Programme Intended Learning Outcomes (PILOs)

Upon successful completion of this Programme, students should be able to:

1. Apply tools and techniques in the development of artificial intelligence software and propose solutions;

2. Apply artificial intelligence concepts and technologies, as well as domain-specific tools and techniques, in the design of quality artificial intelligence systems;

3. Work effectively as member of a team in the development of artificial intelligence systems;

4. Delineate key issues of specific areas in artificial intelligence and develop potential solutions for tackling problems in these areas.

Programme Requirements

Courses in the programme are categorized into Core Courses and Electives. To obtain the award of Master of Science in Artificial Intelligence, students are required to take

all 10 credit units of the Core Courses, AND
at least 21 credit units of the Electives.

Some of the Electives are also designated as Stream Courses of the Autonomous Driving (AD) Stream, Generative AI (GenAI) Stream or Trustworthy AI (TAI) Stream. Students may choose to:

concentrate on a stream by taking 9 or 12 credit units 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 credit units of courses from each of the other streams, OR
take any Electives without concentration on any stream.

The normal study period will be 1 year to complete 31 credit units in full-time mode.

Students may take a 3-credit internship course in summer term of Year 1 and to complete the programme requirements within one year.
Students have the option to complete 25 credit units in the first year, and take an internship course or project course (6 credit units) in the second year.

Year of study

1-Year Study Plan 1 (normal)

1-Year Study Plan 2 (normal)

2-Year Study Plan (optional)

First Year

11 courses

(31 credit units)

10 courses including the 6-credit Project course (31 credit units)

11 courses including the 3-credit Internship course (31credit units)

9 courses

(25 credit units)

Second Year

Nil

Internship/Project course
(6 credit units over 2 semesters)

1. Core Courses (10 credit units)

Course Code	Course Title	Credit Units
CS5491	Artificial Intelligence	3
CS5486	Intelligent Systems	3
CS5489	Machine Learning: Algorithms and Applications	3
CS5611	Seminar on AI Ethics	1

2. Electives (21 credit units)

Course Code	Course Title	Credit Units	Remarks
CS5493	Topics in Autonomous Driving	3	Group I, AD Stream Core
SDSC6007	Dynamic Programming and Reinforcement Learning	3	Group I, AD Stream Core
CS6522	Project in Autonomous Driving	6	Group I, AD Stream Elective
CS6523	Internship in Autonomous Driving	6	Group I, AD Stream Elective
CS6539	Internship in Autonomous Driving	3	Group I, AD Stream Elective
CS6493	Natural Language Processing	3	Group I, GenAI Stream Core
CS5494	Topics in Generative AI	3	Group I, GenAI Stream Core
CS6524	Project in Generative AI	6	Group I, GenAI Stream Elective
CS6525	Internship in Generative AI	6	Group I, GenAI Stream Elective
CS6540	Internship in Generative AI	3	Group I, GenAI Stream Elective
CS5495	Explainable AI	3	Group I, TAI Stream Core
CS5297	Topics in AI Security	3	Group I, TAI Stream Core
CS6526	Project in Trustworthy AI	6	Group I, TAI Stream Elective
CS6527	Internship in Trustworthy AI	6	Group I, TAI Stream Elective
CS6541	Internship in Trustworthy AI	3	Group I, TAI Stream Elective
CS5187	Vision and Image	3	Group II
CS5487	Machine Learning: Principles and Practice	3	Group II
CS6187	Vision and Language	3	Group II
CS6487	Topics in Machine Learning	3	Group II
CS6535	Guided Study in Artificial Intelligence	3	Group II
CS6491	Topics in Optimization and its Applications in Computer Science	3	Group II
CS6528	Internship in Artificial Intelligence	6	Group I
CS6529	Project in Artificial Intelligence	6	Group I
CS6542	Internship in Artificial Intelligence	3	Group I

More information:

All the Project and Internship courses are mutually exclusive.
Students must take 12 CUs before taking a Project course.
After completing at least 22 CUs, students may take a 3-credit Internship course in summer term of their 1^st year of study or may take the Internship course (6 credit units) in their 2^nd year of study.
Students may only take up to 3 courses in Group II electives.

Related Links

Department of Computer Science