MSc Operations Research and Analytics

With study in practice and theory, you'll gain insight into analytics problems faced by businesses, governments, and nonprofits. On the practical side, you'll learn how to model a range of real-world problems using optimisation, stochastic simulation, and machine learning, using specialist software taught in tutorial sessions. On the theoretical side, you'll learn to recognise canonical underlying mathematical problems, and how to solve them with state-of-the-art methods. Courses are taught by faculty members with world-leading research profiles, who can provide insights that will give you a deeper understanding and a competitive edge.

In the first term, you'll learn the fundamentals of operations research and machine learning. In the second term, you can choose from a range of courses in mathematics, statistics, finance, and management. Course topics include algorithms and computation, optimisation, game theory, and further topics in machine learning and AI.

You'll undertake a final project where, working in a consultancy role and using the tools you have learned in the degree, you'll tackle a real problem faced by a partner organisation. Past and present partners include Amazon, BT, British Airways, Emirates Airlines, FICO, Ford Motor Company, Just Eat, Legal and General, the National Audit Office, and Transport for London. As an alternative to the project, more theoretically minded students can write a dissertation supervised by a faculty member.

Revamped for 2025/26, the programme is designed for students wishing to deepen and broaden their mathematics knowledge, and gain skills in high demand in the marketplace.

You're not required to do any preliminary reading in advance of this programme, but if you wish to read some material before arriving, we can make a few suggestions.

If you don't have experience of computer programming, you could learn the language R, which you'll use in ST447 Data Analysis and Statistical Methods. Once you learn any language it's easy to learn others, and programming will be useful in your career. Programming will also give you a sense of what computers can and cannot do, that will be useful in all algorithmic courses. Good starting points are Introductory Statistics with R by Peter Dalgaard, and the Coursera course.

Linear algebra plays a major role in several key courses and in the field of OR generally. It's expected that you're comfortable with the basic notions (linear independence, rank, determinants, solutions of systems of equations, eigenvalues and eigenvectors). These will not be reviewed in the course; you can review this material independently. There are many good textbooks to choose from; a suitable one is Linear Algebra by Martin Anthony and Michele Harvey.