Master of Science in Data Science (MSDS)


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Programme Aims

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 organisational 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.

Programme Intended Learning Outcomes (PILOs):

Upon successful completion of this Programme, students are expected to:

  1. Apply knowledge of science and engineering appropriate to the data science discipline;
  2. Apply contemporary techniques for managing, mining and analyzing data across multiple discipline;
  3. Use computational thinking to discover new knowledge and to solve real-world problems with high complexity;
  4. Recognize the need for and engage in continuous learning about emerging and innovative data science techniques and ideas;
  5. Communicate ideas and findings in written, oral and visual forms and work in a diverse team environment.


Course List (Tentative)

Course Title
Bayesian Data Analysis
Data Analytics for Smart Cities
Dynamic Programming and Reinforcement Learning
Experimental Design and Regression
Exploratory Data Analysis and Visualization
Information Security for eCommerce
Machine Learning
Machine Learning at Scale
Natural Language Processing
Optimization for Data Science
Privacy-enhancing Technologies
Research Projects for Data Science
Statistical Machine Learning I
Statistical Machine Learning II
Storing and Retrieving Data
Time Series and Panel Data

Total Credit required for the MSDS Programme: 30

Remarks: Course offering is subject to sufficient enrolment.


Admission 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 TOEFL score of 550 (paper-based test) or 59 (revised paper-delivered test) or 79 (Internet-based test) on 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


Tuition Fees

HK$8,450 per credit (for local and non-local students admitted in 2019/20)

Total credit units required: 30

Duration of study:
Normal Period Maximum Period
Full-time (1 year) FT (2.5 years)
Part-time (2 years) PT/combined mode (5 years)


Career Prospects

A strong demand of the data scientists and analysts has been recently observed in the worldwide job market. This programme aims at producing analytic and business-aware graduates to meet the growing demand by equipping them with big data analytics skills and nurturing their capability in applying data science techniques to address emerging complicated real-life problems. Upon successful completion of this programme, the student should be able to:

  1. Apply data processing skills to handle data of various formats and sizes.
  2. Conduct comprehensive data analytics with integrating techniques from various disciplines for knowledge discovery and dissemination in organizational decision-making.
  3. Utilize a variety of data visualization techniques to interpret data analytics results.
  4. Demonstrate strong quantitative capabilities as well as communication skills.
  5. Develop descriptive, prescriptive and predictive analytics solutions to tackle emerging challenges in contemporary problems.


Contact Us

Programme Leader

Prof. WANG Junhui


For application enquiries, please contact School of Graduate Studies (SGS) at
For visa matters, please contact Global Services Office (GSO) at


Last modified on 12 February, 2019