Faculty of Business
CODE
23090
SUBCODE
23090-MAF-MAP
ENTRY

Sept 2024 Entry

STUDY MODE
Mixed Mode
DURATION

1.5 years (Full-time)
2.5 years (Part-time)

CREDIT REQUIRED

31

FUND TYPE
Self-Financed

Targeted Taught Postgraduate Programmes Fellowships Scheme    
A total of 12 fellowships shall be awarded to local students. Please click here for details. 

PolyU reserves the right to change or withdraw the fellowship at any time. In case of any dispute/disagreement, PolyU’s decision is final. 

 

Note to Applicants

Please complete all relevant fields and enclose all necessary documents.  
Incomplete applications cannot be processed promptly.

Application Deadline
Local - Mixed Mode
Sept 2024 Entry - 30-Apr-2024
Non-local - Mixed Mode
Sept 2024 Entry - 30-Apr-2024
About Programme
How to Apply
Aims & Characteristics

Programme Aims

This programme starts with the fundamentals of applying analytical techniques to big data to provide decision support for organisations, and progresses to in-depth studies of various application domains.

 

Characteristics

  • Emphasises essential skills and knowledge of business analytics

  • Considers all applications of business analytics

  • Covers theoretical and empirical research on the use of big data in decision making

  • Offers opportunities to use theories to investigate and solve business problems

  • Focuses on systematic development of skills and competence in business analytics

  • Enhances ability to solve problems using big data

  • Empowers students to achieve career potential via professional coaching and career services

Recognition & Prospects

Master of Science in Business Analytics

Curriculum

Programme Structure

Programme Details

For the MSc, students complete 31 credits:

  • 4 Compulsory Subjects (3 credits each)
  • 6 Elective Subjects (3 credits each)
  • 1 Ethics Subject (1 credit)

OR

  • 4 Compulsory Subjects (3 credits each)
  • 2 Elective Subjects (3 credits each)
  • 1 Ethics Subject (1 credit)
  • Research Methods Course (3 credits) and a Dissertation (9 credits)

 

Students may, on completion of 4 Compulsory Subjects and 3 Elective Subjects (21 credits), opt for a Postgraduate Diploma.

 

Areas of Study

The following is a summary of the areas of study.

 

Compulsory Subjects+

  • Business Analytics
  • Business Intelligence and Decisions
  • Management Information Systems
  • Organisation and Management

 

Elective Subjects+@

  • Applications of Decision-making Models
  • Business Applications of Blockchain
  • Business Forecasting
  • Decision Making for Leadership
  • E-Commerce
  • Enterprise Resource Planning
  • 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 (non-credit)

 

Ethics Subject+

  • Business Ethics

 

Information on the subjects can be obtained at https://www.polyu.edu.hk/mm/study/tpg/ba/.

 

+Offerings are subject to class quota availability.

 

@ Student 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/.

 

* Effective 4 May 2020, these subjects have been included in 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: 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 less 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. Classes are normally scheduled on weekday evenings, with some daytime classes for full-time students. Each subject requires 39 contact hours over a teaching semester, with one 3-hour class per week.

Credit Required for Graduation

31

Programme Leader(s)

Programme Director
Prof Xin Xu
BEcon, MPhil, PhD

Deputy Programme Director
Dr Vincent Cho   
BSc, MEngSc, PhD

Subject Area
Business Analytics
Entrance Requirements
  • Applicants should have a Bachelor’s degree or equivalent academic/professional qualifications, preferably with at least one year of relevant work experience.

  • 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.

Enquiries

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

Other Information

Shortlisted candidates may be invited to attend admission interviews.

Initial Registration Credits

3

Programme Leaflet

Please click here to download.

Tuition Fee

HK$333,250 per programme (HK$10,750 per credit) for local and non-local students

Student Message

The recent surge in large language models (LLMs) has reignited a longstanding question: How should we, as humans, position ourselves in a world where machines can perform the majority of intelligent tasks with unprecedented efficiency?

 

Perhaps the same question was asked when the MSc in Business Analytics programme was founded in 2019 – because this curriculum was designed unlike any other similar programmes that the market offers. Instead of spoon-feeding information to students as LLMs do, students who dare to challenge themselves are offered a path to graduate by completing a research paper. This is where originality and imagination are fostered: when students are free to explore their interests and create knowledge with the building blocks they have acquired from foundation courses. This is also where the distinction between humans and bots becomes apparent.

 

In an era where our very existence is being threatened, it is crucial to stay abreast of the challenges ahead. This is also what makes this programme unique – by encouraging innovation and aspiring for creativity that can keep us competitive in an ever-changing world.

MAK Kit Kwan, Isaac (2022/2023 Graduate)

In recent years, business analytics has evolved as a powerful and essential capability for firms in ever-changing and competitive markets. Data has become the new corporate asset. As the sea of data is vast and growing exponentially, executives must connect their data strategy to their analytics strategy to avoid drowning.

 

The MSc in Business Analytics programme aims to build deep competencies in the skills needed to implement and oversee data-driven business decisions. These include (i) collecting, organising, and transforming datasets, (ii) forming inferences and predictions from a vast volume of data, and (iii) improving business decision making through a proficiency with tools such as Python, SmartPLS, and SPSS.

 

As a commercial finance manager in the leading firm in the fast-moving consumer goods industry, I play a strategic role in driving the firm’s financial success. That is why it is essential for me to equip myself with strong analytical skills, mathematical skills, and application skills. I can leverage the knowledge and skills that I have learned from the programme to make extensive use of data to glean valuable insights, predict market changes, and ultimately improve strategic decisions. This enables me to drive business growth so that the firm optimises its margin and remains commercially competitive.

TEA Yin Ee, Agnes (2022/2023 Graduate)
Additional Documents Required
Transcript / Certificate

Both copies of transcripts and certificates are required.

View Other Programmes