BSc (Hons) Mathematics and Computing Bachelor's degree at West London

This module aims to provide a basic knowledge of how to summarise, analyse and interpret data, provide an overview of sampling and experimentation in the mathematical sciences and engineering field, and deliver an introduction to modelling a linear relationship between variables.

This module will introduce you to the fundamentals of software programming using Python. This module forms the basis of other programming modules you will undertake during the course.

An opportunity for you to reflect on the skills and qualities that you already have and to identify those that you need to acquire.

The module provides you with a strong mathematical grounding to prepare you to undertake further mathematics throughout the course. The module will start by covering essential basis of numbers, the application of algebraic and trigonometric principles, application of differential calculus and complex numbers.

You will cover the basics of web design and development, learning how to integrate text, graphics and behaviour to create interactive webpages using HTML5, CSS3 and Javascript. Other aspects will be covered, such as historic development of the web, architecture and basic client server architecture, protocols such as HTTP, issues of accessibility and usability, standards and standardisation organisations (W3C, Internet Working Group) and security (HTTPS, firewalls, certificates).

This module will enable you to read critically, present an argument and distinguish between the quality and suitability of materials. It will prepare you to use and evaluate a range of evidence sources throughout your degree.

This module provides you with the basic mathematical concepts and techniques of discrete structures. It includes the study of mathematical logic, sets, relations and functions. The module will develop your skills in expressing problems in mathematical language, using mathematical techniques to find solutions to problems and communicating mathematical ideas clearly and succinctly.

The aim of this module is to extend your knowledge of matrices, vectors and systems of linear equations and to introduce the abstract concepts of vector spaces, linear maps and inner products.

This module provides a thorough grounding in the fundamentals of Java programming language and object programming concepts. It will focus on the design and build of Java desktop applications using the Java Development Kit and popular Integrated Development Environments, following established industry standard methodologies. The module will have a strong emphasis on using OO modelling techniques to interpret and implement business related applications.

This module introduces you to the most important techniques in Calculus. In particular, the module leads to a deeper understanding of the concepts of differentiation and integration. Tools and techniques for differentiation and integration will be presented in detail.

This module is an introduction to probability theory and statistical methods. The module leads to a deeper understanding of probability distributions, random variables and their role in sampling. Tools such as hypothesis testing are presented and a basic introduction to the statistical software SPSS is provided.

This module will help you to gain the knowledge and competence to deal with basic data structures and algorithms. You will learn how to specify collections using abstract data types (ADTs) and to implement them using a variety of techniques such as linked lists and trees. You'll also use a range of algorithms, including searching and sorting.

The aim of this module is to give you knowledge and techniques for working with vectors and vector fields. You'll extend your understanding of calculus and will be introduced to the concept of multivariable calculus as well as calculus of vectors.

In this module, you will gain insights into key techniques within the field of artificial intelligence (AI). Aspects of AI you will cover include agents, environments and learning as well as techniques such as regression, classification, clustering, reinforcement learning, learning recommendation and decision support systems.

The aim of this module is to provide you with the knowledge and understanding of fundamental concepts of computational theory and computational complexity. You will learn how to examine whether a given problem can be solved computationally. The module aims to introduce computation science, modelling complex dynamic systems and diagramming models.

This module aims to introduce you to the numerical techniques required to solve different mathematical problems motivated by the engineering and the science sector.

This module aims to develop understanding and proficiency in statistical modelling by introducing you to the normal theory linear model. It will provide you with the ability to formulate and apply these models in a range of practical settings, to carry out associated inference appreciating how this relates to the general likelihood inferential framework, and to perform appropriate model selection and model checking procedures.

This module aims to introduce you to abstract algebra starting from basic number theory, moving on to group theory and finally introducing the concept of rings. You will gain familiarity with the underlying theory as well as an understanding a number of applications to computing. Upon completion of the module, you should have a deep understanding of prime factorisation and applications to cryptography, groups and discrete symmetries, rings and factorisation domains.

Under the guidance of an academic supervisor, you will investigate in depth a mathematical or statistical topic with has close links to computing. You will be able to choose a project that may require the solution to a specific problem, the creation of an artefact in a real-world environment or an investigation of innovative ideas and techniques related to an area within their field of study. You will compose a written report and provide an oral presentation on your work.

This module aims to study both the qualitative and quantitative aspects of ordinary and linear partial differential equations.

The module aims to develop an understanding of the elements of non-linear differential equations and dynamical systems. The aim of this module is to expose you to qualitative and quantitative methods for dynamical systems, including nonlinear ordinary differential equations, maps and chaos. The phenomena studied occur in many physical systems of interest.

The module aims to introduce you to linear programming, the Simplex Method and the Transportation Algorithm. The module will enable you to solve linear programming problems as primal problems or using duality. The module includes an introductory theory for nonlinear programming problems by demonstrating the application of Lagrange Multiplier Theory as well as tackling optimisation problems.

The module aims to introduce you to stochastic processes and their applications.

Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience. This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. The emphasis will be on machine learning algorithms and applications, with some broad explanation of the underlying principles.

Software engineering is concerned with the construction of large software programs. This module will bring together the tools and techniques you covered in earlier modules that deal with software development, drawing on concepts from object-oriented and relational design. This module aims to introduce you to software engineering concepts such as software architecture and design and their importance in the implementation of software systems.