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The MSc in Business and Data Analytics (MScBDA) program aims to cultivate students with professional knowledge of business data analytics through active learning of the statistical and analytical methods, real-world business examples, and programming techniques. The program curriculum includes a wide range of knowledge areas such as applied statistics, big data management, data mining, social media analytics, economic and financial forecasting.
The MScBDA program has three streams. Typically, a student will be admitted to either the Quantitative Analysis for Business (QAB) or the Information Systems Management (ISM) streams. Under exceptional circumstances, a student may be considered for admission to the General(G) stream. For information on the MScBDA (ISM) program, please click here. For applicants interested in the QAB steam, please directly apply to the QAB stream through the application system. Only those applicants who state QAB as their first preference will be considered for admission to the QAB stream. We do not allow applicants or future admitted students from other streams to transfer to the QAB stream.
The QAB program (Quantitative Analysis for Business), previously known as MScQAB or MAQAB, has a history of nearly 30 years. The current MScBDA (QAB) program has been developed to provide the modern quantitative skills that will facilitate business problem identification, analytical framework formulation, and statistical analysis in a wide range of areas in the finance industry, technology firms, and public sectors. Many of our graduates have hold managerial positions in business and industrial sectors in Hong Kong. Recent graduate placements include many top companies in mainland China, including Tencent, ByteDance, Nielsen, Earnst and Young, Deloitte, Ping An Asset Management, etc.
The MScBDA (QAB) program offers comprehensive quantitative methods, including courses on applied regression analysis, data mining, predictive modeling in marketing, economic forecasting, and financial econometrics. The program benefits from training students through statistical programmings, such as SAS, R, and Python, and provides hands-on experience for data analytics. All our courses are self-contained and do not require previous programming experience from students. We teach students real-world business examples with relevant data analysis through hands-on programming exercises.
Potential students of the program are college graduates of:
We welcome students who want to pursue a career path where statistical data analysis has a significant role. We have very minimum math requirements for targeting students. However, the potential students are expected to have studied at least one undergraduate course in calculus or linear algebra. We welcome applicants who do not have any background in statistics and programming.