The programme aims to

• enable computer professionals to strengthen and upgrade their technical capabilities in Artificial Intelligence,
• broaden students’ knowledge and deepen their understanding of specific areas in Artificial Intelligence from both the technical and practical perspectives, and
• prepare graduates to take up research and advanced innovative development work in the industry or pursue higher research studies in Artificial Intelligence.

To be eligible for admission, you must satisfy the General Entrance Requirements and have:

• a recognised bachelor's degree in a computing discipline such as Computer Studies, Information Technology, Computer Engineering, Information Systems, or equivalent; or
• a recognised bachelor's degree in a related discipline such as Electronic Engineering, Applied Mathematics, Manufacturing Engineering, Quantitative Analysis, or equivalent, together with applicable working experience in information technology; or
• a recognised bachelor's degree with substantial knowledge or background in information technology.

Applicants whose entrance qualification is obtained from an institution where the medium of instruction is NOT English should also fulfill the following minimum English proficiency requirement:

• 79 (Internet-based test) in the Test of English as a Foreign Language (TOEFL)^@#; or
• an overall band score of 6.5 in International English Language Testing System (IELTS)^@; or
• a score of 450 in the Chinese mainland’s College English Test Band 6 (CET-6); 

^@ TOEFL and IELTS scores are considered valid for two years. Applicants are required to provide their English test results obtained within the two years preceding the start of the University's application period.

^# Applicants are required to arrange with the Educational Testing Service (ETS) to send their TOEFL results directly to the University. The TOEFL institution code for CityUHK is 3401.

Only the above English tests are accepted for MSc Artificial Intelligence (P75) and the following English tests are NOT accepted:

• Duolingo
• GMAT
• GRE
• IELTS Indicator
• TOEFL iBT Home Edition
• TOEIC
• others

Please refer to the updated admissions website for information.

The definitions of non-local applicants and local applicants are set out below:

Non-local Applicants

Persons holding the following documents issued by the Immigration Department (IMMD) of the HKSAR are classified as non-local applicants: 

• Student visa / entry permit; or
• Visa / entry permit under the Immigration Arrangements for Non-local Graduates (IANG Visa); or
• Dependant visa / entry permit for applicants who were 18 years old or above when they were issued with such visa / entry permit by the IMMD

Due to immigration restrictions, nationals from Afghanistan, Cuba, Laos, North Korea (DPRK), Nepal and Vietnam may not be able to obtain a student visa to study in Hong Kong. For details, please click here.

Local Applicants

Persons holding any of the following documents issued by the Immigration Department (IMMD) are classified as local applicants:

• Hong Kong Permanent Identity Card
• Documents issued by the IMMD certifying the right of abode / right to land in Hong Kong
• One-way permit for entry to Hong Kong
• Dependent visa / entry permit for applicants who were below 18 years old when they were issued with such visa / entry permit by the IMMD
• Full-time employment visa / work permit (for part-time study)
• Visa / entry permit for Quality Migrant Admission Scheme (QMAS)
• Visa / entry permit for Capital Investment Entrant Scheme (CIES)
• Visa / Entry permit for Admission Scheme for the Second Generation of Chinese Hong Kong Permanent Residents
• Visa label for unconditional stay

If you need further advice on visa requirements, please contact the IMMD. 

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.

Core Courses (10 credits)

CS5491             Artificial Intelligence

CS5486             Intelligent Systems

CS5489             Machine Learning: Algorithms and Applications

CS5611             Seminar on AI Ethics (1 credit)

Elective Courses (21 credits)

Group I Electives

Autonomous Driving (AD) Stream

CS5493             Topics in Autonomous Driving (AD Stream Core)

SDSC6007        Dynamic Programming and Reinforcement Learning (AD Stream Core)

CS6522             Project in Autonomous Driving (6 credits, AD Stream Elective)

CS6523             Internship in Autonomous Driving (6 credits, AD Stream Elective)

Generative AI (GAI) Stream

CS6493             Natural Language Processing (GAI Stream Core)

CS5494             Topics in Generative AI (GAI Stream Core)

CS6524             Project in Generative AI (6 credits, GAI Stream Elective)

CS6525             Internship in Generative AI (6 credits, GAI Stream Elective)

Trustworthy AI (TAI) Stream

CS5495             Explainable AI (TAI Stream Core)

CS5297             Topics in AI Security (TAI Stream Core)

CS6526             Project in Trustworthy AI (6 credits, TAI Stream Elective)

CS6527             Internship in Trustworthy AI (6 credits, TAI Stream Elective)

Other Group I Electives

CS6528             Internship in Artificial Intelligence (6 credits)

CS6529             Project in Artificial Intelligence (6 credits)            

Group II Electives

CS5187             Vision and Image        

CS5487             Machine Learning: Principles and Practice            

CS6187             Vision and Language  

CS6487             Topics in Machine Learning          

CS6535             Guided Study in Artificial Intelligence  

CS6491             Topics in Optimization and its Applications in Computer Science

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 2^nd year of study, and after completing at least 22 credits.
• Students may only take up to 2 courses in Group II electives.