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Students studying for MSc* award must complete:

Option 1: 6 compulsory subjects (18 credits) and 4 elective subjects (12 credits); OR

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

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) 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) and 1 elective (3 credits) will be awarded a postgraduate diploma.
Subject Code
Subject Name
AMA505 Optimization Methods
AMA563 Principles of Data Science
AMA564 Deep Learning
AMA565 Advanced High Dimensional Data Analysis
COMP5434 Big Data Computing 
COMP5112 Data Structures and Database Systems

Subject Code Subject Name 
AMA502 Operations Research Methods 
AMA506 Graphs and Networks 
AMA507 Mathematical Modelling for Science and Technology 
AMA514A Applied Linear Models 
AMA515A Forecasting and Applied Time Series Analysis 
AMA523 Optimal Control with Management Science Applications 
AMA524 Scientific Computing 
AMA527 Decision Analysis 
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 
 AMA544 Multicriteria Optimization 
 AMA546 Statistical Data Mining 
 AMA566 Advanced Topics in High Frequency Trading 
 AMA567 Quantum Computing for Data Science 
 AMA592 Dissertation 
 COMP5152 Advanced Data Analytics 
 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 HKCAA Ref. Sector Institution Course Title1
 1  42Z129569 POLYU/0324   Science The Hong Kong Polytechnic University-Department of Applied Mathematics

Optimization Methods 

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

 2.  42Z129577 POLYU/0325   Science The Hong Kong Polytechnic University-Department of Applied Mathematics 

Principles of Data Science 

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

 3 42Z129585 POLYU/0326   Science  The Hong Kong Polytechnic University-Department of Applied Mathematics

Deep Learning

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

 4  42Z129593 POLYU/0327   Science  The Hong Kong Polytechnic University-Department of Applied Mathematics

Advanced High Dimensional Data Analysis

[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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