Students
Tuition Fee
HKD 12,900
Start Date
2026-09-01
Medium of studying
Not Available
Duration
1.5 years
Details
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Analytics | Data Science
Area of study
Information and Communication Technologies | Mathematics and Statistics
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
HKD 12,900
Intakes
Program start dateApplication deadline
2026-09-01-
2027-09-01-
About Program

Program Overview


Master of Science in Data Science and Analytics

The Master of Science in Data Science and Analytics is a postgraduate program designed to nurture graduates with expertise across the core disciplines of mathematics, statistics, and computer science.


Programme Details

  • 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
  • Tuition Fees: HK$12,900 per credit for local and non-local students

Programme Leadership

  • Programme Leader: Prof. QI Houduo, BSc, MSc, PhD
  • Deputy Programme Leader: Prof. LIU Yang, BSc, PhD

Aims and Characteristics

Programme Aims

The program aims to develop students' analytical and critical thinking as well as their problem-solving skills, enabling graduates to pursue careers as data analysts in various industries.


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. The program provides a balanced treatment of the three pillars of modern data science: statistics, optimization methods, and computer science.


Admission Criteria

  • Entrance Year: Sept 2026
  • Local Application Deadline: 15 Jan 2026
  • Non-Local Application Deadline: 15 Jan 2026
  • Remarks: Non-local applicants must be registered as full-time students.

Program Structure

The program is designed to cultivate future data analysts with highly developed mathematical, statistical, and computing skills, which are in great demand globally, in both industry and academic settings.


See More