Programme Aims and Objectives

The MSc in Business and Data Analytics (MScBDA) programme aims to cultivate students with professional knowledge of business data analytics through active learning of the theories, methods, supporting techniques across a wide range of knowledge areas such as applied statistics, big data management, data mining and social media analytics. The MScBDA programme has two streams. A student will be admitted to either the Information Analytics Management (IAM) or the Quantitative Analysis for Business (QAB) stream.

Entrance Requirements

Applicants must:

  • hold a recognized Bachelor’s degree in any disciplines with the curricula covering appropriate mathematical knowledge.

Selection will be based on the candidate’s academic performance in previous studies, relevant working experience (if any), motivation and potential of the candidate and performance in the interview.

Applicants whose entrance qualification is obtained from an institution where the medium of instruction is NOT English should also fulfill the following minimum English proficiency requirement:

  • 79 (Internet-based test) in the Test of English as a Foreign Language (TOEFL)@#; or
  • an overall band score of 6.5 in International English Language Testing System (IELTS)@; or
  • a score 450 in the new College English Test (CET6) of Chinese mainland; or
  • other equivalent qualifications.

TOEFL and IELTS scores are considered valid for two years. Applicants are required to provide their English test results obtained within the two years preceding the commencement of the University's application period. 

# Applicants are required to arrange with the Educational Testing Service (ETS) to send their TOEFL results directly to the University. The TOEFL institution code for CityU is 3401.

Course Description

Core Courses

  • Database Management Systems
  • Data Visualization
  • Statistical Data Analysis
  • Data Mining

Information Analytics Management Stream Core

  • Machine Learning and Social Media Analytics

Information Analytics Management Stream Electives

Complete 15 credits with at least 9 credits obtained from the following stream elective courses:

  • Analytical Programming with Python
  • Business Data Analytics
  • Business Intelligence Applications
  • Blockchain Technology and Business Applications
  • Information Systems Project
  • Innovation and Technology Entrepreneurship
  • Knowledge Management
  • Management Support and Business Intelligence Systems
  • Project Management and Quality Assurance

The remaining credits can be obtained by taking postgraduate elective courses offered by any departments in the College of Business.

Quantitative Analysis for Business Stream Core

  • Applied Linear Statistical Models

Quantitative Analysis for Business Stream Electives

Complete 5 electives with at least 4 chosen from the following list:

  • Contemporary Topics in Quantitative Analysis for Business
  • Decision Analytics
  • Managerial Decision Modeling
  • Predictive Analytics with Excel and R
  • Predictive Modeling and Forecasting for Business
  • Predictive Modeling in Marketing
  • Project Management
  • Statistical Modelling in Economics and Finance
  • Statistical Modelling in Risk Management

The remaining elective is a postgraduate course offered by any department in the College of Business.

 

Useful Links

Department of Information Systems

Department of Management Sciences




Remarks:
This programme, jointly offered by the Department of Management Sciences and Department of Information Systems, is housed and coordinated by the College of Business.
This programme has two streams (student will admit to either IAM or QAB).
Admission Code P84
MSc Business and Data Analytics
Mode of study
Combined
tuition fee
Year of entry
2024
Mode of funding
Non-government-funded
Intake target
150
Credit requirement
30
Class schedule
Weekday evenings and possibly Saturday afternoons
Normal study period
Full-time: 1 year
Part-time/Combined mode: 2 years
Max study period
Full-time: 2.5 years
Part-time/Combined mode: 5 years
Mode of processing
Applications are processed on a rolling basis. Review of applications will start before the deadline and continue until all places are filled. Early applications are therefore strongly encouraged.
Level of study
Master's (Taught Postgraduate)
Website
Programme Leader
Prof LAU Yiu Keung Raymond (IAM Stream)
852 34428495
Programme Leader
Prof FENG Guanhao Gavin (QAB Stream)
852 34428645
Programme Leader
Prof DU Lilun (QAB Stream)
852 34427212
General Enquiries
IS General Office (IAM Stream)
852 34428521
General Enquiries
MS General Office (QAB Stream)
852 34428645