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Master of Science in Data Science and Analytics (62027-DFM-DPM)

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Study Pattern

 

Each subject takes place once a week in the evening over a 13-week semester. Full-time students normally take four or five subjects in a semester, whereas part-time students usually take two or three subjects. Some subjects may be offered during the summer to provide students with greater flexibility in designing their own study plan.

 

Students are required to complete 31 credits. Student needs to complete either of the following options:

 

Option 1

  • 18 credits of Compulsory subjects
  • 12 credits of Elective subjects
  • 1 credit of Academic Integrity and Ethics (AIE) subject
  • non-credit bearing National Education (NE) requirement

 

Option 2

  • 18 credits of Compulsory subjects
  • 3 credits of Elective subjects
  • 9 credits of Dissertation
  • 1 credit of Academic Integrity and Ethics (AIE) subject
  • non-credit bearing National Education (NE) requirement

 

Normally, only students who have completed 6 Compulsory subjects (18 credits) and the AIE subject (1 credit) with GPA 3.0 or above at the end of Semester 2 will be considered for Option 2.

 

List of Subjects

All subjects are three-credit based, unless otherwise stated. The table is subjected to finalization. Affected students will be informed if there are further changes.

Compulsory Subjects

COMP5112 Data Structures and Database Systems

COMP5434 Big Data Computing

DSAI5101 Statistical Data Mining

DSAI5102 Principles of Data Science

DSAI5104 Optimization for Machine Learning (subject to approval)

DSAI5207 Modern Deep Learning (subject to approval)

Elective Subjects

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

AMA532 Investment Science

AMA541 Simulation and Risk Analysis

AMA567 Quantum Computing for Data Science

AMA568 Advanced Topics in Quantitative Finance

COMP5152 Advanced Data Analytics

COMP5423 Natural Language Processing

COMP5511 Artificial Intelligence Concepts

COMP5523 Computer Vision and Image Processing

DSAI5103 Advanced High Dimensional Data Analysis

DSAI5201 Artificial Intelligence and Big Data Computing in Practice

DSAI5202 Emerging Topics in Artificial Intelligence and Big Data Computing

DSAI5203 Brain-inspired Computing

DSAI5901 Dissertation (9 credits)

Academic Integrity and Ethics (AIE) Subject

FSN5T01 Academic Integrity and Ethics in Science

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

All subjects are offered at the discretion of subject offering departments, depending on students’ demand and resources available.


 

Programme Requirement Document

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2025/26 Cohort [will be available for DSAI designated staff/students soon]

 

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