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School of Computing and Data Science
Master of Science in Financial Technology and Data Analytics
MSc(FTDA) | Part-time
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Programme Highlights:
Expected Duration
Expected Duration
Fees
Fees
To be updated
Expected Programme Start Date
Expected Programme Start Date
To be updated
Application Deadline
Application Deadline
Description
Description
Apply
Expected Duration
Expected Duration
2 years
Fees
Fees
Self-funded:
Local: HK$270,000
Non-local: HK$360,000
*A ‘non-local’ student is a person entering Hong Kong for the purpose of education with a student visa/entry permit issued by the Director of Immigration.
Expected Programme Start Date
Expected Programme Start Date
2025 September
Application Deadline
Application Deadline
Round 1 (Main):
12:00 AM (GMT +8), January 03, 2025
Round 2 (Clearing):
12:00 noon (GMT +8), April 11, 2025
Description
Description
Most classes will be held on weekday evenings or during weekends.
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Overview

The Master of Science in Financial Technology and Data Analytics programme aims to prepare students for a career in the ever-changing world of FinTech. It has an interdisciplinary curriculum by drawing on the expertise from diverse areas of engineering, business, law and statistics, with a technology focus. Through the courses, students will gain essential FinTech skills necessary for navigating the changing landscape of the finance industry, as well as knowledge of the hottest industry trends.

Graduates of the programme would learn new competencies in new technologies such as AI (artificial intelligence), blockchain, big data analysis, financial fraud analytics, etc. Knowledge and skills gained from completing this programme will place our graduates in an excellent position to advance their career. They are expected to be well prepared for a wide range of jobs that require strong technological skills in finance-related industries.

Students are required to complete not fewer than 75 credits nor more than 84 credits to graduate.

Entrance Requirements

1. A Bachelor's degree in Engineering or Science discipline or an equivalent qualification

Download Documents

For additional information, we recommend reviewing the following documents:

Additional Information
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Regulations & Syllabuses
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Supporting Documents
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Faculty

School of Computing and Data Science
To meet the growing importance of computing and AI literacy in the 21st century, HKU recognises the need to equip students with the necessary skills to succeed in an increasingly technology-driven world. The newly established School of Computing and Data Science (SCDS) at The University of Hong Kong encompasses the existing Department of Computer Science and the Department of Statistics and Actuarial Science. We have about 60 renowned scientists and 800 postgraduate students and offer 14 academic programmes.

The School, through a cross-faculty integration, will create a powerful synergy between computational technology, mathematical modelling and statistical reasoning that have become the cornerstones of modern data science and artificial intelligence. By combining the complementary strengths of computer science and statistics curricula, students graduating from the school will have strong analytical and computational skills. The School will also serve as a thriving hub for interdisciplinary academic and research collaborations, fostering partnerships with all other faculties that leverage the potential of modern data science and AI.

The taught postgraduate programmes offered by the School will provide students with the latest knowledge and skills in computing & data science technologies and prepare them for the demands of the industry and job market. The programmes will cover various topics, including but not limited to data science, artificial intelligence, cybersecurity, statistics and software engineering301. The School works closely with industry partners to ensure that the programmes are up-to-date and relevant to the current demands of the industry. The school aims to produce well-equipped graduates who can contribute significantly to advancing knowledge and innovation.
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Contacts

If you have any inquiries regarding the programme or faculty, please do not hesitate to reach out to us using the contact methods provided below:

Programme Admissions Advisor(s)
Dr KP Chow
telephone 3917 1828
Contact Info
Miss Ellen Lam
telephone 3917 1828