In our programme, students are able to develop strong critical thinking, analytical, logical and problem solving skills which open doors to a wide career prospects ranging from business, industry, government, scientific research and much more. A variety of tools such as mathematical modelling, numerical analysis, calculus, discrete mathematics, ordinary differential equations, linear algebra, actuary, decision modeling and statistics are learnt by our students to solve a wide range of problems arise in economy, finance, business management, social sciences and health, to name a few.

In our programme, students will use modelling and prediction, then turn both masses of everyday information, and more specialized quantitative and qualitative data, into actionable insights. By using mathematical models and analytical reasoning, students able to examine problems in areas such as operations and supply chain management, information technology, marketing, finance, management, manufacturing, and economics. Students will learn how to solve these problems by using a number of mathematical techniques, including optimization methods (linear, integer, nonlinear), computer simulation, decision analysis, artificial intelligence, data-mining, and more.

This programme has been designed as a platform for statistics enthusiasts to explore various statistical methods while being equipped with key skills to solve real-life problems. The structured courses which include inferential statistics, regression modelling, and sampling techniques, among many others, will empower students to conduct analytical research methods. Therefore, able to identify and work with patterns in data, eventually interpreting the results, and making informed conclusions. Students are then able to translate information into meaningful insights that can be used by companies and organisations in various areas like banking, finance, data analytics, insurance, business consultancy, manufacturing as well as in the government service. Ultimately, students are well prepared for the data-driven world.