Sept 2027 Entry
1.5 years (Full-time)
2.5 years (Part-time)
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(To be confirmed) The programme has been selected by the University Grants Committee (UGC) for the Hong Kong Future Talents Scholarship Scheme for Advanced Studies. Local students admitted to this programme can apply for the scholarship, please click here for details.
Early Round: 2026-10-20
Main Round: 2027-02-25
Early Round: 2026-10-20
Main Round: 2027-02-25
What's New
- Taught Postgraduate
- Undergraduate
- Undergraduate
Programme Aims
This programme starts with fundamentals of applying analytical techniques on big data for decision supports of an organisation, and progresses to in-depth studies of various application domains.
Characteristics
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Emphasises essential skills and knowledge of business analytics
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Applies domains of business analytics
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Covers theoretical knowledge and research findings on decision-making using big data
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Offers opportunities to apply theories to the investigation and solving of business problems
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Focuses on systematic training and the development of skills and competence in business analytics
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Teaches skills to solve big data problems
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Empowers students to achieve their career potential via professional coaching and career services
Master of Science in Business Analytics
Programme Structure
Programme Details
For the MSc, students complete 31 credits:
- 4 Compulsory Subjects (3 credits each)
- 6 Elective Subjects (3 credits each)
- 1 AIE Subject (1 credit)
OR
- 4 Compulsory Subjects (3 credits each)
- 2 Elective Subjects (3 credits each)
- 1 AIE Subject (1 credit)
- The subject Research Methods (3 credits) and a Dissertation (9 credits)
Students may graduate with a Postgraduate Diploma upon completing 4 Compulsory Subjects, 1 AIE subject and 3 Elective Subjects (22 credits).
Areas of Study
The following is a summary of the areas of study.
Compulsory Subjects+
- Business Analytics*
- Business Intelligence and Decisions*
- Management Information Systems*
- Organization and Management*
Elective Subjects+@
- Applications of Decision Making Models
- Business Applications of Blockchain
- Business Forecasting
- Decision Analytics by Machine Learning
- Decision Making for Leadership
- E-Commerce
- Entrepreneurship
- Enterprise Resource Planning
- Field Study for Business Management
- Managing Operations Systems
- Marketing Management
- Models for Decision Making
- Research Methods
- Seminars in Emerging Technology
- Social Media Marketing
- Strategic Management
- Technology Innovation and Management
- Textual Analytics in Business
- MM MSc Career Workshop (0 credit)
AIE Subject+
- Academic Integrity and Ethics in Business (non-chargeable)
Information on the subjects can be obtained at https://www.polyu.edu.hk/mm/study/tpg/ba/.
+ Offerings are subject to class quota availability.
@ Students may also choose from a list of “Common Pool Electives”, subject to the requirements of the programme curriculum. For details, please refer to www.polyu.edu.hk/fb/study/tpg-landing/common-pool-electives/.
* These subjects have been included on the list of reimbursable courses under the Continuing Education Fund. The programme (MSc in Business Analytics) is recognised under the Qualifications Framework (QF Level 6).
Note: The programme structure and content are subject to continuous review and change.
Mode of Study and Duration
Mode of study: Mixed-mode
Students may pursue their studies with either a full-time study load (taking 9 credits or more in a semester) or a part-time study load (taking fewer than 9 credits in a semester).
Students normally complete the programme full-time in 1.5 years or part-time in 2.5 years. Students who wish to extend their studies beyond the normal duration can submit a request to their Department/Faculty for consideration.
The programme offers a structured progression. Students are encouraged to follow this progression to benefit from the cohort-based structure. Classes are normally scheduled on weekday evenings, with some daytime classes for full-time students. Each 3-credit subject requires 39 contact hours over a teaching semester, with one 3-hour class per week.
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Programme Director
Prof. Xin Li
BE, ME, PhD
Deputy Programme Director
Dr Vincent Cho
BSc, MEngSc, PhD
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Applicants should have a Bachelor’s degree or equivalent academic/professional qualifications, preferably with at least one year of relevant work experience.
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Applicants, normally aged 27 or above, with other post-secondary qualifications and at least 6 years of work experience in industry, commerce or public administration, including 3 years in a managerial capacity, will also be considered.
If you are not a native speaker of English, and your Bachelor's degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the University’s minimum English language requirement for admission purpose. Please refer to the "Admission Requirements" section for details.
For further information, please contact:
Tel: (852) 2766 7381 / (852) 2766 7108
Email: mm.msc@polyu.edu.hk
For academic matters, please contact:
Dr Vincent Cho
Tel: (852) 2766 6339
Email: vincent.cho@polyu.edu.hk
Prof. Xin Li
Tel: (852) 2766 4067
Email: x.li@polyu.edu.hk
Shortlisted candidates may be invited to attend admission interviews.
Please click here to download.
HK$399,000 per programme (HK$13,300 per credit) for local and non-local students
* The 1-credit AIE Subject is non-chargeable.
MM Taught Postgraduate Scholarship Scheme
• Entry Scholarship available for applicants with outstanding academic and non-academic performance.
• Successful awardees may receive a full tuition fee waiver.
• Non-local applicants may be eligible for an additional living allowance of up to HK$50,000.
• Please click here for details.
PolyU reserves the right to change or withdraw the scholarship at any time. In case of any dispute/disagreement, PolyU’s decision is final.
We live in an era of rapid technological advancement, where AI and new tools are increasingly shaping the way we work and live. In this fast-changing environment, the ability to adapt, learn continuously, and embrace innovative approaches has become essential for personal and professional growth.
The MSc in Business Analytics programme at PolyU helped me gain hands-on experience with analytical tools such as SPSS, SmartPLS, and coding-based projects. The programme emphasised practical application, which allowed me to work on real-world problems and develop skills that go beyond theory.
The guidance from professors and the support of peers were invaluable. Coming from a more theoretical background, I witnessed how this programme transforms students from diverse fields, helping us build confidence, analytical thinking, and teamwork skills. The collaborative environment fosters personal growth in ways I had never imagined.
I am deeply grateful for the mentorship, friendships, and experiences that shaped my journey. Today, as I apply these skills in the financial sector, I carry forward not only technical expertise but also the inspiration and values nurtured at PolyU.
Coming from a non-data background, transitioning into a data analyst role was a deliberate choice, and PolyU's MSc in Business Analytics gave that transition a solid academic foundation.
This programme stands out in how seamlessly it bridges business thinking with analytical depth. Studying part-time while working full-time, I could immediately apply what I learned, from machine learning models to forecasting techniques, directly to workplace challenges. The curriculum never lets you choose between being a business professional and a data practitioner; it trains you to be both.
The breadth of subjects also surprised me. Alongside core analytics, I engaged with topics such as blockchain applications, textual analysis, risk management, and business ethics, giving me a fuller picture of how data-driven decisions operate within broader organisational and ethical contexts.
For anyone coming from a non-technical background, this programme is genuinely accessible yet intellectually demanding. It gave me the confidence and credentials to grow in my career, and the structured learning helped me connect experiences I had accumulated in practice with frameworks that made me a sharper, more well-rounded analyst.
Both copies of transcripts and certificates are required.
