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  4. MSc in Business Analytics (23090-MAF/MAP)
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MSc in Business Analytics (MAF/MAP)

Programme Structure


For MSc, students complete 31 credits

  • 4 Compulsory Subjects (3 credits each)
  • 1 AIE Subject (1 credit)
  • 6 Elective Subjects (3 credits each)
    OR
  • 4 Compulsory Subjects (3 credits each)
  • 1 AIE Subject (1 credit)
  • 2 Elective Subjects (3 credits each)
  • the subject Research Methods (3 credits) and a Dissertation (9 credits)

 

Students may, on completion of 4 Compulsory Subjects, 1 credit of AIE Subject and 3 Elective Subjects (22 credits in total), opt for the Postgraduate Diploma.

From 2024/25 Cohort onwards

  • MM5112 Organization and Management*
  • MM5412 Business Intelligence and Decisions*
  • MM5424 Management Information Systems*
  • MM5425 Business Analytics*
  • MM5T21 Academic Integrity and Business Ethics (non-chargeable)

Non-Dissertation Option

  • MM501 Research Methods
  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM576 Marketing Management
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)

Dissertation Option

  • MM501 Research Methods (3 credits)
  • MM594 Business Analytics Dissertation (9 credits)
  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM576 Marketing Management
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)

2023/24 Cohort

  • MM5112 Organization and Management*
  • MM5412 Business Intelligence and Decisions*
  • MM5424 Management Information Systems
  • MM5425 Business Analytics*

  • MM5021 Business Ethics

Non-Dissertation Option

  • MM501 Research Methods
  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM576 Marketing Management*
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)

 

Dissertation Option

  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM576 Marketing Management*
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)
  • MM501 Research Methods (3 credits)
  • MM594 Business Analytics Dissertation (9 credits)

2022/23 Cohort

  • MM5112 Organization and Management*
  • MM5412 Business Intelligence and Decisions*
  • MM5424 Management Information Systems
  • MM5425 Business Analytics*


  • MM5021 Business Ethics

Non-Dissertation Option

  • MM501 Research Methods
  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM5453 Transformation to Sustainable Smart Cities
  • MM576 Marketing Management*
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)

Dissertation Option

  • MM5203 Decision Making for Leadership
  • MM531 Strategic Management
  • MM534 Entrepreneurship 
  • MM5413 Business Forecasting
  • MM5426 Business Applications of Blockchain
  • MM5427 Textual Analysis in Business
  • MM5433 Decision Analytics by Machine Learning
  • MM544 E-Commerce
  • MM5451 Technology Innovation and Management
  • MM5452 Seminars in Emerging Technology
  • MM576 Marketing Management*
  • MM5831 Social Media Marketing
  • LGT5102 Models for Decision Making
  • LGT5105 Managing Operations Systems
  • LGT5113 Enterprise Resource Planning
  • LGT5122 Applications of Decision Making Models
  • MM5913 Field Study for Business Management
  • MM5400 Launchpad to Advanced Analytics (0 credit)
  • MM5995 MM MSc Career Workshop (0 credit)
  • MM501 Research Methods (3 credits)
  • MM594 Business Analytics Dissertation (9 credits)

  
    • The offering of subjects is subject to class quota availability. Students may also choose from a list of "Common Pool Electives", subject to the prescriptions of programme curriculum.
    • Programme structure, course names and content are subject to continuous review and change.
    cef_logo * 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).

 

Mode of Study and Duration

Mode of study: Mixed-mode

Students can pursue their studies with either a full-time study load (9 credits or more in a semester) or a part-time study load (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 the Department of Management and Marketing for consideration.

The programme offers a structured progression pattern. Students are encouraged to follow the pattern to benefit from the cohort-based structure. 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.

Current students can refer to the Programme Requirement Document for more details about the programme.

 

Programme Requirement Document

 Programme Requirement Document 2024/2025  BA_24_25
Programme Requirement Document 2023/2024 Cover 2223_BA
Programme Requirement Document 2022/2023 Cover 2223_BA
Programme Requirement Document 2021/2022 BA_21_22
Programme Requirement Document 2020/2021 BA_20_21
Programme Requirement Document 2019/2020 BA_19_20
 

 


 

Messages from Alumni

The MSc in Business Analytics programme has been an invaluable experience that has fully prepared me for the realities of working as a business analyst. Unlike many programmes on the market, the MSc in Business Analytics strikes an ideal balance between imparting foundational theories and equipping students with technical methodologies. Notably, the curriculum ensures that graduates can effectively translate skills and knowledge into practical applications for real-world business challenges.

By combining hands-on projects and case studies, I was able to build a portfolio demonstrating my ability to clean and understand complex data, construct predictive models, and translate data-driven insights into practical business recommendations. This applied learning approach honed my analytical mindset and presentation skills – capabilities that I believe will be highly transferable to any future role in my career path. The curriculum also ensures proficiency with industry-relevant languages and tools, including SQL, SPSS, Python, and SmartPLS.

Overall, this programme offers a solid foundation for prospective business analysts to develop both the essential skill sets and the necessary business acumen to thrive in this dynamic industry. The experience has been incredibly enjoyable and rewarding.

CHEUNG Suet Ngan, Florence

(2023/24 Graduate)
Florence CHEUNG BA

The MSc in Business Analytics programme has been an invaluable experience that has fully prepared me for the realities of working as a business analyst. Unlike many programmes on the market, the MSc in Business Analytics strikes an ideal balance between imparting foundational theories and equipping students with technical methodologies. Notably, the curriculum ensures that graduates can effectively translate skills and knowledge into practical applications for real-world business challenges.

 

By combining hands-on projects and case studies, I was able to build a portfolio demonstrating my ability to clean and understand complex data, construct predictive models, and translate data-driven insights into practical business recommendations. This applied learning approach honed my analytical mindset and presentation skills – capabilities that I believe will be highly transferable to any future role in my career path. The curriculum also ensures proficiency with industry-relevant languages and tools, including SQL, SPSS, Python, and SmartPLS.

 

Overall, this programme offers a solid foundation for prospective business analysts to develop both the essential skill sets and the necessary business acumen to thrive in this dynamic industry. The experience has been incredibly enjoyable and rewarding.

Li Tsz Man Lavina

(2023/24 Graduate)
Lavina LI BA
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(852) 2766 7381 / (852) 2766 7108
mm.msc@polyu.edu.hk

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