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:
- Apply knowledge of science and engineering appropriate to the data science discipline;
- Apply contemporary techniques for managing, mining and analyzing data across multiple discipline;
- Use computational thinking to discover new knowledge and to solve real-world problems with high complexity;
- Recognize the need for and engage in continuous learning about emerging and innovative data science techniques and ideas;
- Communicate ideas and findings in written, oral and visual forms and work in a diverse team environment.
Course List (Tentative)
|Bayesian Data Analysis|
|Business Data Analytics|
|Computer Networks and Internets|
|Data Analytics for Smart Cities|
|Data Management and Blockchain|
|Database Management Systems|
|Dynamic Programming and Reinforcement Learning|
|Experimental Design and Regression|
|Exploratory Data Analysis and Visualization|
|Information Security for eCommerce|
|Machine Learning at Scale|
|Natural Language Processing|
|Optimization for Data Science|
|Research Study 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.
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
HK$8,450 per credit (for local and non-local students admitted in 2019/20)
Total credit units required: 30
|Normal Period||Maximum Period|
|Full-time (1 year)||FT (2.5 years)|
|Part-time (2 years)||PT/combined mode (5 years)|
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:
- Apply data processing skills to handle data of various formats and sizes.
- Conduct comprehensive data analytics with integrating techniques from various disciplines for knowledge discovery and dissemination in organizational decision-making.
- Utilize a variety of data visualization techniques to interpret data analytics results.
- Demonstrate strong quantitative capabilities as well as communication skills.
- Develop descriptive, prescriptive and predictive analytics solutions to tackle emerging challenges in contemporary problems.
Last modified on 5 November, 2018