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Programme Structure

Medium of instruction: Chinese supplemented with English

For MSc, students complete 31 credits

  • 4 Compulsory Subjects (3 credits each)
  • 1 Ethics Subject (1 credit)
  • 6 Elective Subjects (3 credits each)
    OR
  • 4 Compulsory Subjects (3 credits each)
  • 1 Ethics 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 and 3 Elective Subjects (21 credits), opt for the Postgraduate Diploma.

From 2023/24 Cohort onwards

  • 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
  • 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
  • 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
  • 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
  • MM5995 MM MSc Career Workshop (0 credit)
  • MM501 Research Methods (3 credits)
  • MM594 Business Analytics Dissertation (9 credits)

From 2022/23 Cohort onwards

  • 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
  • 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
  • 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
  • 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
  • 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 Fundwith effect from 4 May 2020. 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 normal duration can submit such request to the Department of Management and Marketing for consideration, as appropriate.

The programme offers a structured progression pattern. Classes are normally scheduled on weekday evenings. 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 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 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

(2022/23 Graduate)
Winny Mok_resized_200x200

I could feel the magic of data when taking subjects related to business analytics. This programme let me know how to use data analysis tools and methods in real-life business especially for making decisions. Case studies helped me look at business from different perspectives and find solutions using different methods. I developed rigorous and divergent thinking during the process of learning.

WU Lin, Lily

(2019/20 Graduate)
lily_wu

Combining academic rigour and practical relevance helped me understand the role of data in decision-making and the fundamentals of applying analytical techniques on big data for decision supports of an organisation. This programme enabled me to apply the latest academic thinking and analytical tools in making business decisions.

REN Dongzhe, Jenny

(2019/20 Graduate)
jenny_ren

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

(2022/23 Graduate)
Ma Dickson_resized_200x200
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General Enquiries
(852) 2766 7381 / (852) 2766 7108
mm.msc@polyu.edu.hk

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