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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 2025/26 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
  • 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
  • MM5995 MM MSc Career Workshop (0 credit)

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*

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*


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 3-credit 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 digital age has arrived in full force. We’re witnessing a true transformation in how businesses operate, with the digital revolution poised to reshape entire industries and job markets in the coming decades. This reality makes it essential for professionals like you and me to adapt through continuous learning.

PolyU’s MSc in Business Analytics programme offers a well-structured platform for doing just that. Its curriculum blends domain-specific business knowledge with cutting-edge data analytics tools—a balanced approach that goes beyond the usual divide between technical skills and operational experience. You’ll learn from faculty who bring expertise from business, academia, and technology, and who regularly share developments in AI and machine learning that extend far beyond textbook theory.

If you’re transitioning from a traditional industry, this programme provides both an accessible introduction to analytical techniques and a forward-looking perspective on technological evolution.

Another key strength is the connections you’ll build. Collaborating with talented peers from diverse sectors, you’ll gain first-hand insights into how digital technologies are reshaping industries. You’ll also engage in thoughtful discussions about the ethical and practical implications of these changes. These experiences will mould you into a business analyst who combines deep field knowledge with technological fluency to create meaningful impact.

Learning is a lifelong journey of discovery. I’m deeply grateful to PolyU for this pivotal experience—one that has helped me make sense of my professional journey, broaden my perspective, develop new skills, and build the confidence to navigate the challenges of tomorrow.

 

HU Yue

(2024/25 Graduate)
HU Yue BA

The MSc in Business Analytics programme has been a transformative journey that has shaped both my analytical thinking and professional confidence. The curriculum strikes a balance between theory and practice, equipping students with the skills they need to thrive in data-driven roles.

Training in industry-standard tools such as Python, SQL, SPSS, SmartPLS, and everyday tools like Excel strengthened my technical skills and prepared me to meet the demands of today’s job market. What sets this programme apart is its emphasis on developing essential business analytics and problem-solving skills—essential for translating data into meaningful insights and making informed decisions in a competitive field.

What I found most valuable was the focus on experiential learning. Through case studies, group projects, and hands-on assignments, I applied analytical techniques to complex business challenges. These experiences helped me better understand how data can be used to drive strategy and improve outcomes in business contexts.

I’m grateful for the enriching academic environment and dedicated faculty support, especially through networking events. These interactions connected me with industry leaders and alumni, further enriching my professional development. This programme has laid a strong foundation for my career and given me the confidence to pursue new opportunities in the fast-evolving field of business analytics.

 

 

YUNG Kin Yi Queenie

(2023/24 Graduate)
YUNG Kin Yi Queenie BA
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General Enquiries
(852) 2766 7381 / (852) 2766 7108
mm.msc@polyu.edu.hk

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