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Computational Data Science

Programme Code
Study Period
Open for
Programme Code
Study Period
4 Years
Open for
JUPAS / Non-JUPAS Year 1 / Mainland (Gaokao) / International
Programme Introduction

Make Data-Driven

The data-driven era has created strong interest in and a need for analysing, storing, distributing and sharing massive amounts of data using sophisticated data analytics and machine-learning algorithms and methodologies, with applications in multiple disciplines, including science, social science, finance, public health, medicine, engineering and telecommunications. We have witnessed huge demand for data analysts in both local and global employment markets. However, designing proper data-driven solutions for analysing and interpreting massive amounts of information remains a non-trivial challenge, since it requires in-depth knowledge of both computing methodologies and statistical principles for problem solving, data collection, data modelling and analysis, and scientific experimental design.

The CDAS programme is designed to develop mathematical, technical and analytical skills to create solutions to lead data-driven decision making. It aims to equip students with the capabilities of applying both: (1) high-performance parallel and distributed computing for big data manipulation, and (2) data-driven statistical procedures, methodologies and theories for mining patterns, making predictions, and discovering patterns and insights from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with a solid foundation in data structure and algorithms, parallel and distributed computing system programming, statistical modelling and analysis, and large-scale statistical inferences.

The CDAS programme emphasizes the computational foundations of data science, providing an in-depth understanding of algorithms and data structures for storing, manipulating, visualizing, interpreting and learning from large datasets. Four specialized streams are offered for students to choose application fields according to their interests:

  • Computational Data Science
  • Computational Physics
  • Computational Medicine
  • Computational Social Science


#10 globally in Computer Science (#1 in Hong Kong)
(US News and World Report Best Global Universities by Subject in 2023)

#6 in Statistics in Asia (51-75 globally)
(Academic Ranking of World Universities by academic subject in 2022)

Career Prospects

Computational data science is a rapidly evolving interdisciplinary field that is in high demand. Future graduates will be prepared for careers that create order and derive meaning from huge amounts of data. This programme prepares graduates for careers that require deep knowledge and skills in machine learning, database management, and high-performance computing, with an adequate statistics background. Future alumni can work as business intelligence analysts, data mining engineers, data modelers, data scientists, engineers and developers, data warehouse architects, research analysts, etc.

The CDAS programme aims to admit high calibre students who demonstrate outstanding ability in English, mathematics and science. An excellent academic background, together with a problem-solving mindset, is essential for understanding the knowledge and tackling future challenges related to global issues.

If you are interested in this programme, please review the application requirements and deadlines specific to the respective admission scheme to increase your chances of getting accepted.


More Information:

Department of Computer Science and Engineering:

Department of Computer Science and Engineering, Room 1028, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, NT, Hong Kong

(852) 3943 4269

Department of Statistics:

Department of Statistics, Room 119, Lady Shaw Building, The Chinese University of Hong Kong, Shatin, NT, Hong Kong

(852) 3943 7931