Master of Science in Data Science

Year of Entry


Application Deadline

Application Closed

Mode of Study


Mode of Funding


Indicative Intake Target


Minimum No. of Credits Required


Class Schedule

Weekday evenings

Normal Study Period

Full-time: 1 year;
Part-time: 2 years;

Maximum Study Period

Full-time: 2.5 years;
Part-time/Combined mode: 5 years;

Mode of Processing

Applications are processed on a rolling basis. Review of applications will start before the deadline and continue until all places are filled. Early applications are therefore strongly encouraged.
Programme Leader
Prof WANG Junhui
PhD (University of Minnesota)
General Enquiries
+852 3442 7887
Programme Aims and Objectives

The programme aims to produce data-analytic and business-aware graduates to meet the growing demand for high-level data science skills and to prepare graduates to apply data science techniques to knowledge discovery and dissemination in organizational decision-making. It is also intended to help established data analytic professionals upgrade their technical management and development skills and to provide a solid path for students from diverse fields to rapidly transition to data science careers.

Entrance Requirements

Applicant must be a degree holder in Engineering, Science or other relevant disciplines, or its equivalent

Non-local candidates from an institution where medium of instruction is not English should fulfill one of the following English proficiency requirements.

  • a score of 550 (paper-based test) or 59 (revised paper-delivered test) or 79 (Internet-based test) in the Test of English as a Foreign Language (TOEFL); or
  • an overall band score of 6.5 in International English Language Testing System (IELTS); or
  • a minimum score of 450 in band 6 in the Chinese mainland’s College English Test (CET6); or
  • other equivalent qualifications


Fellowships Scheme

Fellowship awards are available for local students admitted to this programme under the Fellowships Scheme supported by the HKSAR Government. This programme in the priority area of “Research and Innovation” is one of the targeted programmes listed under the Fellowships Scheme with 9 fellowship awards. Local students admitted to the programme in full-time, part-time or combined study mode will be invited to submit applications for the fellowships. 

Course Description

Core Courses (15 credit units)

  • Exploratory Data Analysis and Visualization
  • Research Projects for Data Science
  • Statistical Machine Learning I
  • Statistical Machine Learning II
  • Storing and Retrieving Data

Electives (15 credit units)

  • Bayesian Data Analysis
  • Data Analytics for Smart Cities
  • Dynamic Programming and Reinforcement Learning
  • Experimental Design and Regression
  • Information Security for eCommerce
  • Machine Learning
  • Machine Learning at Scale
  • Natural Language Processing
  • Optimization for Data Science
  • Privacy-enhancing Technologies
  • Storing and Retrieving Data
  • Time Series and Panel Data

Remarks: Course offering is subject to sufficient enrolment.


The full MSc degree award requires 30 credit units, with the completion of taught courses only, or taught courses plus the dissertation project.

Useful Links
† Combined mode: Local students taking programmes in combined mode can attend full-time (12-18 credit units per semester) or part-time (no more than 11 credit units per semester) study in different semesters without seeking approval from the University. For non-local students, they will be admitted to these programmes for either full-time or part-time studies. Non-local students must maintain the required credit load for their full-time or part-time studies and any changes will require approval from the University.