- Year 1
Learn high-level mathematical and statistical skills and master industry software including Matlab and Maple right from the start. You’ll begin by building on the mathematical skills and topics you learnt at school, studying six core modules including calculus, linear algebra, numerical methods, pure mathematics, and probability and statistics. We’ve structured the curriculum so that all of our students acquire a common mathematical expertise. You’ll also be able to explore your interests with the flexibility to move between courses as you progress.
BPIE113 Stage 1 Mathematics Placement Preparation
The route to graduate-level employment is found easier with experience. These sessions are designed to assist students in their search for a year-long placement and in their preparation for the placement itself. Such placements are optional but strongly recommended.
MATH1601 Mathematical Reasoning
This module introduces the basic reasoning skills needed to develop and apply mathematical ideas. Clear logical thinking is central to the understanding of mathematics. The module explores fundamental properties of prime numbers, their random generation and use in modern cryptography.
MATH1602 Calculus and Analysis
This module covers key topics in calculus and analysis and prepares students for the rest of their degree. It has an emphasis on proof and rigour and introduces some multi-dimensional calculus together with the reasoning skills needed for the development of modern mathematics. Analysis is the rigorous underpinning of calculus and these key ideas are developed and applied to limits of sequences, series and functions.
MATH1603 Linear Algebra and Complex Numbers
This module explores the concepts and applications of vectors, matrices and complex numbers. The deep connection between algebra and geometry is explored. The techniques that are presented in this module are at the foundation of many areas of mathematics, statistics, physics, and several other applications.
MATH1605 Probability with Applications
An understanding of uncertainty and random phenomena is becoming increasingly important nowadays in daily life and for a variety of fields. The aim of this module in probability is to develop the concept of chance in a mathematical framework. Random variables are also introduced, with examples involving most of the common distributions and the concepts of expectation and variance of a random variable.
MATH1610 Numerical and Computational Methods
This module provides an introduction to appropriate mathematical software, computational mathematics and creating simple computer programs. Students will use mathematical software interactively and also write programs in an appropriate computer language. The elementary numerical methods which underlie industrial and scientific applications will be studied.
MATH1611 Geometry and Group Theory
This module will introduce the foundations of group theory, elementary geometric topology, and Euclidean geometry.
- Year 2
modules including advanced calculus, analysis, ordinary differential equations,
a case study-based introduction to operational research and Monte Carlo
techniques. An advanced statistical module helps you to build on and develop
your existing knowledge and expertise.
BPIE213 Stage 2 Mathematics Placement Preparation
These sessions are designed to help students obtain a year-long placement in the third year of their programme. Students are assisted both in their search for a placement and in their preparation for the placement itself.
MATH2601 Advanced Calculus
In this module the geometrical and dynamical concepts needed to describe higher-dimensional objects are introduced. This includes vector calculus techniques and new forms of integration such as line integration. Students also explore the relations between integration and differentiation in higher dimensional hyperspaces. This knowledge is applied to various real world problems.
MATH2602 Statistical Inference and Regression
The module provides a mathematical treatment of statistical inference, including confidence intervals and hypothesis testing. Methods of estimation are explored, focusing on maximum likelihood estimation. The module also demonstrates the underlying mathematical theory of the general linear model, through a variety of applications, using professional software.
MATH2603 Ordinary Differential Equations
The module aims to provide an introduction to different types of ordinary differential equations and the analytical and numerical methods needed to obtain their solutions. Extensive use is made of computational mathematics packages. Applications to mechanical and chemical systems are considered as well as the chaotic behaviour seen in climate models.
MATH2604 Mathematical Methods and Applications
Vector calculus is extended to higher dimensions and applied to a range of important scientific problems primarily from classical mechanics and cosmology. Differential and integral calculus is applied to the solution of differential equations and the orthogonal functions bases are constructed. The crucial mathematical concepts of integral transforms (Fourier and Laplace) and Fourier series are introduced.
MATH2605 Operational Research and Monte Carlo Methods
This module gives students the opportunity to work on open-ended case studies in operational research (OR) and Monte Carlo methods, both of which are important methods in, for example, industry and finance. It allows students to work on their own and in teams to develop specific skills in OR and programming as well as refining their presentation and communication skills. The skills in computational simulation developed in this module have many applications.
MATH2606 Real and Complex Analysis
This module deepens the student’s understanding of real analysis and introduces complex analysis. The important distinction between real and complex analysis is explored and the utility of the complex framework is demonstrated. The central role of power series and their convergence properties are studied in depth. Applications include the evaluation of improper integrals and the construction of harmonic functions.
- Optional placement year
Take an optional but highly recommended paid placement year. Your placement will provide valuable professional experience, enhancing your employability and making your CV really stand out. Previous placement with world renowned companies have included the Department for Communities and Local Government, Fujitsu, GlaxoSmithKline, Vauxhall Motors, Liberty Living and Eli Lilly.
BPIE331 Mathematics and Statistics Placement
A 48-week period of professional training is spent as the third year of a sandwich programme while undertaking an approved placement with a suitable company. This provides an opportunity for the student to gain experience of how mathematics is used in a working environment, to consolidate their previous study and to prepare for the final year and employment after graduation. Recent placement providers include GSK, the Office for National Statistics, NATS (air traffic control) and VW Group.
- Final year
between several different project modules in mathematics, statistics or both,
or opting to study a school-based module. Your studies will focus on a diverse
range of topics from partial differential equations and optimisation to
a wide variety of statistical modules including medical and Bayesian
statistics. After graduating, you’ll have the skills and experience needed to
begin your career, or to take a research degree – often including funded places
on MSc's in medical and financial statistics.
MATH3613 Data Modelling
This module provides an employment relevant tool box of statistical modelling techniques and a rigorous treatment of the underlying mathematics. The Bayesian framework for statistical inference is developed and compared with the classical approach. Important computational algorithms, including Markov Chain Monte Carlo, are described. Application-rich modelling problems are considered.
MATH3614 Medical Statistics
The content includes the design and analysis of clinical trials, including crossover and sequential designs and an introduction to meta-analysis. Epidemiology is studied, including case-control and cohort studies. Survival analysis is covered in detail. Computer packages are used throughout.
MATH3623 Financial Statistics
This module introduces students to the concepts and methods of financial time series analysis and modelling and to a variety of financial applications. The module reviews the necessary univariate and multivariate time series models and inferential techniques. Model selection, forecasting and the ‘curse of dimensionality’ problem for high dimensional modelling are treated both analytically and computationally. The R programming language is widely used in this module.
MATH3603 Professional Experience in Mathematics Education
This module provides an opportunity for final year students to gain experience in teaching and to develop their key educational skills by working in a school environment for one morning a week over two semesters.
MATH3604 Geometry and Algebra
A review of group theory leads into an exploration of plane affine, hyperbolic, and projective geometries, all from the Kleinian point of view. Then an introduction to rings and fields is given with applications in geometry emphasised. These topics are key ideas in the study of pure mathematics.
MATH3605 Partial Differential Equations
This module introduces partial differential equations using real-life problems. It provides a variety of analytic and numerical methods for their solution. It includes a wide range of applications including heat diffusion and the Tsunami wave.
MATH3606 Classical and Quantum Mechanics
All of physics and a large part of applied mathematics is based on classical mechanics and its extension to quantum theory. This module introduces key ideas of these topics to students with a mathematics background. An overarching theme is the key role of symmetry, both for classical motion and quantum behaviour.
MATH3609 Optimisation, Networks and Graphs
This module introduces the mathematics of continuous and discrete optimisation. It provides the theoretical background and practical algorithmic techniques required to model and solve a diverse range of problems.
MATH3611 Electrodynamics and Relativity
This module introduces Maxwell's theory of electromagnetism and Einstein's theory of special relativity. It includes a wide range of applications of electromagnetism, the Lorentz transformations and some of the apparent paradoxes of relativity together with their resolution. It also explains why E = mc^2.
MATH3616 Professional Experience in Industry
This module provides an opportunity for students to gain experience in applying mathematics in a commercial setting by undertaking a summer placement. Students develop their skills in written and verbal communication, listening, problem solving, time management, teamwork and leadership. Recent summer placement providers include Babcock International, BMW Group, Chess Dynamics Ltd and South West Water.
MATH3627 Mathematical Statistics in Context
In this module students will perform structured investigations on a variety of advanced topics in mathematical statistics. Written and oral presentations of the work will be made.
Students who have identified a topic of particular interest have the opportunity to study it in a final year project. Students work individually and independently, with help and advice from a supervisor, on the chosen topic. The project is assessed through presentations and the preparation of a dissertation. This is a major piece of work and the project counts as two modules
Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.
The following programme specification represents the latest course structure and may be subject to change:
The modules shown for this course are those currently being studied by our students, or are proposed new modules. Please note that programme structures and individual modules are subject to amendment from time to time as part of the University’s curriculum enrichment programme and in line with changes in the University’s policies and requirements.
In light of the Coronavirus (COVID-19) pandemic, the changeable nature of the situation and any updates to government guidance, we may need to make further, last minute adjustments to how we deliver our teaching and learning on some or all of our programmes, at any time during the academic year. We want to reassure you that even if we do have to adjust the way in which we teach our programmes, we will be working to maintain the quality of the student learning experience and learning outcomes at all times.