The course prepares graduates to understand the context, importance and relevance of big data problems facing a business and solve them using a variety of statistical, operational research and machine learning techniques. The overriding objective of the programme is to train students to solve business problems and obtain actionable business insight using analytics. Combining academic rigour and practical relevance, the programme is a careful balance of teaching and learning, individual and group work. Case study methodology and class'based discussions are used to strengthen the conceptual, analytical and problem solving skills of the participants in real situations. In addition, there are regular seminars by external expert speakers.
Modules include: introduction to data analytics; data analysis tools; statistics and econometrics; optimisation and decision models; databases and distributed systems; network analytics; machine learning; visualisation; capstone business analytics group project; business analytics report; career and professional skills. Optional modules include: logistics and supply'chain analytics; digital marketing analytics; workforce analytics; financial analytics; healthcare and medical analytics; retail and marketing analytics.
Course Additional Entry
A 1st or upper 2nd Class Honours degree (or international equivalent), in a quantitative discipline such as mathematics, statistics, computer science, engineering, physics, economics, business or a quantitative social science. Although work experience is not a requirement, prospective students are strongly recommended to undertake relevant internships and work placements, as this adds weight to their application. Candidates who are currently in employment are expected to demonstrate how undertaking the programme will help to develop their career. There is no GMAT requirement.
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