Program Overview

Master of Science in Data Science and Analytics

The Master of Science in Data Science and Analytics is a postgraduate program designed to equip students with the knowledge and skills necessary to succeed in the field of data science and analytics.

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.

Programme Requirements

Students are required to complete 31 credits. There are two options to fulfill this requirement:

• 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 list of subjects is as follows:

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
• DSAI5207 Modern Deep Learning

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.