Faculty of Computer and Mathematical Sciences
CODE
62037
SUBCODE
62037-FAI-PAI
ENTRY

Sept 2027 Entry

STUDY MODE
Mixed Mode
DURATION

1 year (Full-time)
2 years (Part-time)

CREDIT REQUIRED

31

FUND TYPE
Self-Financed
  • Non-local applicants must be registered as full-time students.

  • The subjects offered will depend on the availability of teaching resources and the number of students registered.

  • The programme has been selected by the University Grants Committee (UGC) for the Hong Kong Future Talents Scholarship Scheme for Advanced Studies. Local students admitted to this programme can apply for the scholarship, please click here for details.

Application Deadline
Local - Mixed Mode
Sept 2027 Entry
Early Round: 2026-10-20
Main Round: 2027-02-25
Non-local - Mixed Mode
Sept 2027 Entry
Early Round: 2026-10-20
Main Round: 2027-02-25

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About Programme
How to Apply
Aims & Characteristics

Programme Aims

Artificial intelligence and big data (AIBD) technologies are experiencing rapid development in society and industry. Combining technologies from computer science and machine learning, this programme is designed to teach students how to understand and create value from AIBD.

 

The objectives of the programme are listed below:

  • To provide students with knowledge of AIBD from the perspective of research and practical applications, and

  • to meet the increasing market demand for high-quality personnel with expertise in AIBD computing in Hong Kong.

 

Characteristics

  • The programme focuses on research on and applications of AIBD.

  • It comprises a core set of subjects on AIBD programming and practices, as well as various elective subjects in the related areas.

 

Flexible modes of study are available (full-time or part-time).

Recognition & Prospects

Graduates of this programme are expected to possess the necessary knowledge to pursue careers in AIBD application areas, such as smart cities, e-commerce, sales and marketing, banking and other related industries. Notable potential employers include Alibaba, Tencent, NVIDA, SenseTime, Insilico Medicine, Lalamove, Cathay Pacific, etc.

Curriculum

Programme Structure

Students must complete: 
Option 1: 5 Compulsory Subjects (15 credits) and 5 Elective Subjects (15 credits); OR 
Option 2: 5 Compulsory Subjects (15 credits), 2 Elective Subjects (6 credits) and a Dissertation (9 credits)

 

There is also a 1-credit compulsory subject, Academic Integrity and Ethics in Computer and Mathematical Sciences.

 

Students who opt for the Dissertation should have completed 4 subjects with good academic results. Normally, only students who have completed 4 subjects (12 credits) and the AIE subject (1 credit) with a GPA of 3.0 or above at the end of Semester One of their first year will be considered for Option 2.

 

Details of the programme structure and information on the subjects offered can be obtained at DSAI website.

Credit Required for Graduation

31

Programme Leader(s)

Programme Leader
Prof. CHUNG F.L. Korris
BSc, MPhil, PhD, MIEEE

 

Deputy Programme Leader
Prof. HUA Wen
BEng, PhD

Subject Area
Artificial Intelligence and Big Data Computing
Entrance Requirements
  • A Bachelor’s degree in Computing/Computer Science/Engineering, Information Systems, Mathematics or other related disciplines.

  • Applicants with a Bachelor’s degree in other disciplines with at least 3 years of relevant work experience in IT will also be considered.

 

If you are not a native speaker of English, and your Bachelor's degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the University’s minimum English language requirement for admission purpose. Please refer to the "Admission Requirements" section for details.

Enquiries

Tel: (852) 3400 3274
Email: dsai.tpg@polyu.edu.hk

 

For more information, please visit our website.

Tuition Fee

HK$13,500 per credit for local and non-local students

(Note: There is no tuition charge for the 1-credit Academic Integrity and Ethics subject.)

Student Message

I have met professors with a passion for both teaching and research while studying for the MSc in Artificial Intelligence and Big Data Computing. My experiences at PolyU have given me exposure to AI and distributed learning. The convenient campus has also allowed me to digest knowledge gained in the classroom and generate new knowledge in the shade of a tree or take a break at Victoria Harbour before embarking on a new round of academic challenges.

Shan Yimeng
Additional Documents Required
Employer's Recommendation

Preferred but not compulsory

Transcript / Certificate

Copies of transcripts, graduation certificates and other relevant certificates are required.

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