Mathematics

The module provides an introduction to operational research and its methodology. It covers topics on methodology and modelling, linear programming, non-linear optimisation, project planning, decision trees, financial calculations and an introduction to graphs and networks to include minimal spanning trees and shortest path algorithms and maximal flow.

This module provides you with a range of essential skills to ensure that you are adequately prepared for undergraduate study and to enhance their employability attributes.

This module studies the logic, set-theory, function and number concepts necessary for understanding mathematics.

This module studies single-variable calculus and associated topics in analysis. Calculus and analysis underpin many other areas of mathematics and applications in mathematical modelling. The use of proof and different proof techniques are studied throughout the module.

This module teaches you basic statistics in a style that will prepare you for second year work, making use of relevant statistical software. It covers descriptive statistics, probability and statistical applications. 

This module extends the work on matrices and vectors that you will have met previously and introduces you to programming with MATLAB®. It covers topics such as vectors, matrices and the design and implementation of MATLAB programs.

This module provides an introduction to a range of numerical methods and mathematical modelling making use of relevant software. It also enhances your employability skills, such as communication, teamwork, planning and organisation. 

This module extends the calculus to functions of several variables and studies other analytical methods such as Laplace transforms and Fourier series.

This module further develops the linear algebra from the first year, which has its basis in matrices and vectors and is a fundamental branch of mathematics with a wide range of applications in finance, cryptography, computing and more.

This module develops statistical techniques and introduces formal methods of inference and estimation. Interest rate calculations, portfolio modelling and option pricing, with reference to the stochastic nature of asset prices are introduced.

An introduction to number theory focusing on results in modular arithmetic and prime numbers. An introduction to classical and modern cryptography and how aspects of number theory are applied there.

You are required to study independently, research new topics and manage their own learning. Employability skills are embedded throughout this module. Specific elements of the assessment are tuned to encourage the use of soft skills, giving oral and poster presentations and writing reports.

This module introduces you to more advanced techniques in Operational Research, building on knowledge and methods that they have learnt at Level 4 and Level 5. 
 
Industrial applications are used to illustrate methods and use of professional software made. 

This module extends the knowledge of mathematical modelling and deepens the understanding of dynamical systems theory with applications using a computer package. There are applications in biology, chemistry, computer science, economics, electrical and mechanical engineering, nonlinear optics, and physics in general which will help with student employability.

This module provides and introduction to numerical techniques for solving Partial Differential Equations (PDE).

The module develops the study of a broad range of computational methods for the solution of stiff and non-stiff systems of Ordinary Differential Equations (ODEs), together with the underlying Computational Linear Algebra methods and relevant applications in research and industry.

This module extends your knowledge of statistical techniques and deepens their understanding of statistical modelling by introducing a range of models which might be fitted to data commonly encountered in the real world.