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This university-level mathematics module covers key topics including calculus, vectors, matrices, sequences and functions, and assumes you are confident with the underpinning algebraic ideas.

An introduction to essential topics – such as proof, differential equations, mechanics and discrete mathematics – and an opportunity to extend your knowledge of calculus and its applications.

Introduces and helps integrate key ideas from statistics, algebra, geometry and trigonometry into your everyday thinking to build your confidence in learning and using mathematics.

This module develops the mathematical foundations for our engineering qualifications, covering essential algebra, trigonometry, calculus, complex numbers and matrices in an engineering context.

This OU level 2 module, for those with prior mathematical knowledge, introduces the main topics of pure mathematics: group theory, linear algebra and analysis.

Learn statistical tools and quantitative methods, covering topics such as summarising data; examining relationships; randomness and sampling distributions; probability; testing hypotheses; and estimation.

This introductory physical sciences module will provide a taste of classical and quantum physics, astronomy, planetary science and cosmology, and introduce you to computer programming.

Study how to make data-driven decisions using analytic reasoning, descriptive data analysis, hypothesis testing, modelling of relationships in the data, and forecasting techniques.

Solve real problems by transforming them into mathematical models and learning methods of solution, including vector algebra, differential equations, calculus, matrices and numerical methods.

Solve real problems by transforming them into mathematical models and learning methods of solution, including differential equations, linear algebra and vector calculus.

This module explores basic statistical concepts for analysing and interpreting data, emphasising the practical but includes some of the underlying theory.

This module introduces medical statistics, time series analysis, multivariate data analysis, and Bayesian statistics – broadening your perspective on practical modern statistics.

This module provides a broad introduction to number theory; the algebraic theory of rings and fields; and the theory of distance or metrics for mathematical objects.

This computational applied mathematics module develops computer programming skills to find numerical solutions to mathematical problems.

This innovative and flexible module allows you to count different types of learning such as OpenLearn towards a formal OU qualification.

Learn about modelling simple fluid flows, ordinary and partial differential equations and mathematical methods that can be used to solve fluid-flow problems.

This module provides you with the mathematical underpinning for practical applications of statistical techniques, and interpretation of data and statistical analyses.

This module will develop your knowledge and understanding of the teaching of mathematics, with an emphasis on Key Stage 3, and broaden your ideas about how people learn and use mathematics.

This module develops the theory of functions of a complex variable, emphasising their geometric properties and indicating some applications.

This module covers core topics in the application of mathematics and is an accessible introduction to the study of applied mathematics at OU level 3.

Learn about important ideas in the learning and teaching of geometry; how geometric thinking develops; and how to analyse this from a mathematics teacher’s perspective.

This module will develop your awareness of using symbols and equip you with educational ideas to analyse algebraic reasoning, teaching and learning.

This module is about discrete mathematics and its applications to modelling and solving real-world problems, e.g. the famous Travelling Salesman Problem.

Discover how models can describe the occurrences of events – from a gambler’s ruin or the positions of plants, to the spread of an epidemic.

M348 is an applied statistics module focusing on general linear and generalised linear modelling.