Data Science

Your first year provides background knowledge and fundamental skills in Data Science, including coverage of areas such as mathematical analysis, probability, set theory and linear algebra, which are further embedded in your second year. From this point you will also acquire more specialist expertise, gaining practical experience of industrial software engineering through group project work. You’ll also hone your mathematical skills through the study of more advanced mathematical techniques such as stochastic processes, multivariate calculus, randomisation and metrics. Your final year is focused on applying all these skills, culminating in an individual project on a topic of your choice, involving extended analysis of a substantial data set.

How will I learn?

You will learn through a combination of lectures, small-group tutorials and practical sessions based in the Department's well-equipped undergraduate computing laboratory. A central part of learning in Mathematics and Statistics is problem solving. We encourage and guide students in tackling a variety of theoretical exercises and computing tasks. MMathStat students work on their own research project in Statistics, supervised by academic staff.

How will I be assessed?

You will be assessed by a combination of closed and open-book examinations, continuous assessment and project work, depending on your options.