Overview
Introduction
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.
Preliminary readings
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.
Entry requirements
An upper second class honours (2:1) degree in a relevant discipline (or equivalent). Students should normally have taken university courses including calculus, linear algebra, and statistics. Appropriate work experience will also be considered.
Please select your country from the dropdown list below to find out the entry requirements that apply to you.
Overseas
English language requirements
The English language requirement for this programme is Standard. Read more about our English language requirements.
Competition for places at LSE is strong. So, even if you meet the minimum entry requirements, this does not guarantee you an offer of a place.
However, please don’t feel deterred from applying – we want to hear from all suitably qualified students. Think carefully about how you can put together the strongest possible application to help you stand out from other students.
Programme content
You'll take three compulsory courses and will choose courses from a range of options within the Department and across other relevant departments, including Management and Statistics.
Year 1
Courses to the value of one and a half units from a range of options
Why study with us
Discover more about our students and department.
Meet the department
The Department of Mathematics aims to be a leading centre for the study of mathematics in the social sciences.
The department has a vibrant intellectual community, with fantastic students, internationally respected academics and high-achieving alumni. Our department has grown rapidly in recent years, with exciting developments in research and new teaching programmes and courses.
This research encompasses four main overlapping areas:
- discrete mathematics and algorithms
- mathematical game theory
- financial and related mathematics
- operational research.
All aspects of our research were ranked world-leading or internationally excellent in the most recent Research Excellence Framework (2021), submitted jointly with the Department of Statistics.
We embrace the School’s ethos of research-led teaching. Currently, we offer four undergraduate and three postgraduate programmes, as well as doctoral research opportunities on our MPhil/PhD in Mathematics. These programmes are all in high demand – attracting talented students from diverse backgrounds.
Our programmes are highly interdisciplinary and we have close ties with other departments at LSE, including Statistics, Economics, Finance, Management and the Data Science Institute.
Whatever your study route, you’ll benefit from a welcoming, inclusive and friendly learning environment where students and staff are supported to achieve their best.
Learn more about our programmes, recent research and regular events and seminars.
Why LSE
University of the Year 2025 and 1st in the UK
Times and The Sunday Times - Good University Guide 20251st in London for the 13th year running
The Complete University Guide - University League Tables 20256th In the world
QS World University Rankings by Subject 2024Carbon Neutral In 2021, LSE became the first Carbon Neutral verified university in the UK
Your application
Overview
We welcome applications from all suitably qualified prospective students. At LSE, we want to recruit students with the best academic merit, potential and motivation, irrespective of background.
We carefully consider each application and take into account all the information included on your application form, such as your:
- academic achievement (including predicted and achieved grades)
- statement of academic purpose
- two academic references
- CV.
See further information on supporting documents.
You may need to provide evidence of your English language proficiency. See our English language requirements.
When to apply
Applications for this programme are considered on a rolling basis. This means that applications will close once the programme is full.
There is no fixed deadline. However, if you’d like to be considered for any funding opportunities, you must submit your application (and all supporting documents) by the funding deadline. See the fees and funding section below for more details.
Fees and funding
The table of fees shows the latest tuition fees for all programmes.
You're charged a fee for your programme. At LSE, your tuition fee covers registration and examination fees payable to the School, lectures, classes and individual supervision, lectures given at other colleges under intercollegiate arrangements and, under current arrangements, membership of the Students' Union. It doesn't cover living costs or travel or fieldwork.
Learning and assessment
How you learn
How you're assessed
All taught courses are required to include formative coursework which is unassessed. It is designed to help prepare you for summative assessment which counts towards the course mark and to the degree award. LSE uses a range of formative assessment, such as essays, problem sets, case studies, reports, quizzes, mock exams and many others. Summative assessment may be conducted during the course or by final examination at the end of the course. An indication of the formative coursework and summative assessment for each course can be found in the relevant course guide.
Graduate destinations
Overview
This programme is ideal preparation for a range of careers in quantitative positions in consultancy, management, finance, government and business, anywhere in the world.
Further information on graduate destinations for this programme
Top 5 sectors our students work in:
Career support
From CV workshops through to careers fairs, LSE offers lots of information and support to help you make that all-important step from education into work.
Many of the UK’s top employers give careers presentations at the School during the year and there are numerous workshops covering topics such as job hunting, managing interviews, writing a cover letter and using LinkedIn.
See LSE Careers for further details.