Master of Science in Data Science and Analytics (62027-DFM-DPM)
Entrance Year Sept 2026
Programme Code 62027
Stream Code
DFM (Full-time)
DPM (Part-time)
Mode of Study Mixed Mode
Normal Duration
1.5 years (Full-time)
3 years (Part-time)
Fund Type Self-Financed
Credits Required for Graduation
31
Local Application Deadline
15 Jan 2026 *
Early Round: 2025-10-15
Main Round: 2026-01-15
Extended Round: 2026-04-30
Non-Local Application Deadline
15 Jan 2026 *
Early Round: 2025-10-15
Main Round: 2026-01-15
Extended Round: 2026-04-30
Tuition Fees
HK$12,900 per credit for local and non-local students
(Note: There is no tuition charge for the 1-credit Academic Integrity and Ethics subject.)
Programme Leader(s)
Programme Leader
Dr JIANG Binyan
BSc (USTC), PhD (NUS)
Remarks
Non-local applicants must be registered as full-time students.
Aims and Characteristics
Programme Aims
In today’s era of big data, large data sets are generated every day in various areas of society and industry, from social networking to finance. It is challenging to extract and analyse information from such an unprecedentedly large volume of data. To create value from such data, one must combine techniques from mathematics, statistics and computer science. This programme nurtures graduates with expertise across the core disciplines of mathematics, statistics and computer science. It develops students’ analytical and critical thinking as well as their problem-solving skills. This enables graduates to pursue careers as data analysts in various industries, such as finance and information technology.
Characteristics
Data science and analytics involve the use of mathematical, statistical and computing techniques to extract useful information from large-scale data and make decisions accordingly. Statistics, optimisation methods and computer science are widely acknowledged to form the three pillars of modern data science. This programme is designed to provide a balanced treatment of these three pillars, with the aim of cultivating future data analysts.
Graduates with highly developed mathematical, statistical and computing skills are in great demand globally, in both industry and academic settings.
