MSc Data Science

Year of Entry


Application Deadline

Local & Non-local : 31 Mar 2023

Mode of Study


Mode of Funding


Indicative Intake Target


Minimum No. of Credits Required


Class Schedule

Weekday evenings and Saturday afternoons
(plus weekday daytime sessions if necessary)
Evening classes normally start at 7:00 p.m.

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
Dr TAN Matthias Hwai-yong
BEng(UTM), MEng(NUS), PhD(Georgia Tech)
General Enquiries
+852 3442 7887
Programme Aims and Objectives

The Master of Science in Data Science (MSDS) programme aims to produce data-analytic 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 data analytic professionals upgrade their technical management and development skills, and to provide a solid path for students from related quantitative fields to rapidly transition to data science careers.

Programme Intended Learning Outcomes (PILOs):

Upon successful completion of this Programme, students should be able to:

  1. Apply knowledge of science and engineering appropriate to the data science discipline
  2. Understand theoretical foundation of contemporary techniques and apply them for managing, mining and analyzing data across multiple disciplines
  3. Comprehend computational tools and use data-driven thinking to discover new knowledge and to solve real-world problems with complex structures
  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
Entrance Requirements

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

Applicants whose entrance qualification is obtained from an institution where the medium of instruction is NOT English should also fulfill the following minimum English proficiency requirement:

  • a score of 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 score of 450 in the Chinese mainland’s College English Test Band 6 (CET-6); or
  • other equivalent qualifications.

^ Effective from 11 April 2021, the TOEFL revised paper-delivered test is no longer offered.

@ TOEFL and IELTS scores are considered valid for two years. Applicants are required to provide their English test results obtained within the two years preceding the start of the University's application period.

# Applicants are required to arrange with the Educational Testing Service (ETS) to send their TOEFL results directly to the University. The TOEFL institution code for CityU is 3401.

In view of the recent development of COVID-19, ‘TOEFL iBT Home Edition’ and ‘IELTS Indicator’, as indicated below, are accepted as equivalent qualifications for the fulfillment of the University’s minimum English proficiency requirement for admission to TPg programmes with immediate effect for 2023/24 cohort:

  • TOEFL iBT Home Edition: a score of 79; or
  • IELTS Indicator: an overall band score of 6.5
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” is one of the targeted programmes listed under the Fellowships Scheme with 7 fellowship awards. Local students admitted to the programme in full-time, part-time or combined study mode may 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
  • Data Mining and Knowledge Discovery
  • Data-driven Operations Research
  • Deep Learning
  • Dissertation
  • Dynamic Programming and Reinforcement Learning
  • Experimental Design and Regression
  • Information Security for eCommerce
  • Machine Learning: Principles and Practice
  • Machine Learning at Scale
  • Natural Language Processing
  • Networked Life and Data Science
  • Online Learning and Optimization
  • Optimization for Data Science
  • Predictive Analytics and Financial Applications
  • Privacy-enhancing Technologies
  • Social Foundations of Data Science
  • Statistical Methods for Categorical Data Analysis 
  • Stochastic Optimization for Machine Learning
  • Time Series and Recurrent Neural Networks
  • Topics in Financial Engineering and Technology

Remarks: Programme electives will be offered subject to availability of resources and sufficient enrolment.


Our MSDS programme offers comprehensive and rigorous training for students seeking a profession in data science. Our graduates have embarked on exciting and highly rewarding careers such as data scientists, data analysts, data engineers, AI engineers, professional consultants, managers, and other data expert positions. These careers, which have excellent prospects for growth and high compensation, are in high demand in industries such as finance and banking, technology, real estate, insurance, education, e-commerce, retail and marketing, and transportation and logistics.


Our graduates from the past few years have found employment in prestigious companies that include members of the Big Four accounting firm, tech giants, retail giants, and international banks. Moreover, they are shouldering critical roles that involve the use of data science to aid highly impactful tasks such as strategic business and operations decision-making, and innovative product and process development. Their careers spread across Hong Kong, the USA, and Mainland China (e.g. Beijing, Ningbo, Chongqing, Shanghai, and Shenzhen, etc.) Around 60% of our surveyed graduates receive a monthly salary of over HKD$30,000. Some of our graduates are also furthering their studies in PhD programmes at world-renowned universities.


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.