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Students studying for MSc* award must complete:

Option 1: 6 compulsory subjects (18 credits), 4 elective subjects (12 credits) and 1 Academic Integrity and Ethics subject (1 credit); OR

Option 2: 6 compulsory subjects (18 credits), 1 elective subject (3 credits), a dissertation (9 credits) and 1 Academic Integrity and Ethics subject (1 credit)

Students who opted for the dissertation should have completed 6 compulsory subjects with good academic results. Normally, only students who have completed 6 compulsory subjects (18 credits) and 1 Academic Integrity and Ethics subject (1 credit) with GPA 3.0 or above at the end of Semester 2 will be considered for (Option 2).

*Students who do not complete the programme but have passed 6 compulsory subjects (18 credits), 1 elective (3 credits) and 1 Academic Integrity and Ethics subject (1 credit) will be awarded a postgraduate diploma.
Subject Code
Subject Name
AMA505 Optimization Methods
AMA546 Statistical Data Mining
AMA563 Principles of Data Science
AMA564 Deep Learning
COMP5112 Data Structures and Database Systems
COMP5434 Big Data Computing

Subject Code Subject Name 
AMA502 Operations Research Methods
AMA507 Mathematical Modelling for Science and Technology
AMA514A Applied Linear Models
AMA515A Forecasting and Applied Time Series Analysis
AMA524 Scientific Computing
AMA528 Probability and Stochastic Models
AMA529 Statistical Inference
AMA531 Loss Models and Risk Analysis
AMA532 Investment Science
AMA541 Simulation and Risk Analysis
AMA542 Advanced Operations Research Methods
AMA565 Advanced High Dimensional Data Analysis
AMA566 Advanced Topics in High Frequency Trading
AMA567 Quantum Computing for Data Science
AMA568 Advanced Topics in Quantitative Finance
AMA569 Stochastic Models for Carbon Pricing and Trading
AMA592 Dissertation
COMP5152 Advanced Data Analytics
COMP5423 Natural Language Processing
COMP5511 Artificial Intelligence Concepts

The list of Reimbursable Courses for the purpose of Continuing Education Fund is as follows. Note that (i) These courses have been included in the list of reimbursable courses under the Continuing Education Fund (這些課程已加入持續進修基金可獲發還款項課程名單內) AND (ii) These courses / The mother course (The Master of Science in Data Science and Analytics) of this module are recognised under the Qualifications Framework (QF Level [6]) (這些課程 / 本單元所屬之主體課程(數據科學及分析理學碩士)在資歷架構下獲得認可(資歷架構第[6]級).

No. CEF Course Code Institution Course Title1
 1 42Z129569 The Hong Kong Polytechnic University

Optimization Methods

[Module from Master of Science in Data Science and Analytics]

 2 42Z129577 The Hong Kong Polytechnic University

Principles of Data Science

[Module from Master of Science in Data Science and Analytics]

 3 42Z129585 The Hong Kong Polytechnic University

Deep Learning

[Module from Master of Science in Data Science and Analytics]

 4 42Z159867 The Hong Kong Polytechnic University

Statistical Data Mining

[Module from Master of Science in Data Science and Analytics]


Students of these CEF-reimbursable courses may apply for subsidies from the government via
https://www.wfsfaa.gov.hk/cef/en/index.htm

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