Course summary

This challenging degree takes your study of Mathematics and Statistics to Master’s level. It is the ideal choice if you are considering postgraduate study or a career that requires high-level numeracy skills or research. The MMath combines a strong mathematical grounding with the latest developments in statistics and machine learning to provide the foundation you’ll need to step into a data-driven workplace. The first two years follow a similar structure to the BSc. The wider range of modules introduced in Years 3 and 4 explore more sophisticated mathematical and statistical techniques in greater depth. The course is based in a brand-new facility, purpose-built to meet the learning, teaching and study needs of students from the Department. You will be taught by a team of mathematicians and statisticians with a wealth of experience in industry and research. The Department is home to a number of research groups with specialisms in both pure and applied mathematics. With many members of the teaching team actively involved in research there are plenty of opportunities to link learning to the latest research in distinctive and creative ways. The first year begins with a broad-based introduction to pure and applied mathematics, statistics and probability and provides a sound foundation for in-depth study in subsequent years. As you move into the second and third year the focus on statistics increases. During the final year you complete a double-module project. This can be the individual project in which you tackle a theoretical area or an applied problem in depth. Alternatively, the internship project is a statistics and machine learning piece of work based on a third-party problem. Both projects can be carried out in collaboration with external organisations to add valuable real-world context to your degree. Year 1 The first year consists of 100 compulsory Mathematics credits: -Analysis (20) -Calculus (20) -Linear Algebra (20) -Dynamics (10) -Probability (10) -Programming (10) -Statistics (10) Together with a further 20 credits. The first-year Mathematics modules expand and develop topics that may be familiar from A level (or equivalent), smoothing the transition to university study. Fundamental statistical methodologies are developed from first principles in the Statistics and Probability modules, providing a mathematical language and coherent conceptual framework with which to structure subsequent developments. Other modules equip you with the essential mathematical tools needed for further study. Year 2 In the second year, you will take four compulsory modules (60 credits): -Analysis in Many Variables (20) -Statistical Inference (20) -Data Science and Statistical Computing (10) -Statistical Modelling (10) Together with a further 60 credits which can be chosen from a wide range. The four compulsory modules will furnish you with the central mathematical, inferential, modelling, and computational tools needed for modern statistics and machine learning, as well as looking at important surrounding issues such as data governance. Further modules allow you to broaden or deepen your knowledge of particular topics or techniques. Year 3 In the third year, you choose from a range of modules on topics central to modern statistics and machine. Year 4 In the fourth year, you take a 40-credit capstone project module, tackling a theoretical area or an applied problem in particular depth. Subject to availability, this may be performed in collaboration with a company or other organisation. For the remaining 80 credits, you choose from a range of modules focusing on topics of current research interest. Placement Year You may be able to take a work placement. Find out more: https://www.dur.ac.uk/study/ug/studyoptions/