Mathematics and Computing with Foundation Year BSc (Hons)

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.

The 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'll cover include agents, environments and learning as well as techniques such as regression, classification, clustering, reinforcement learning, learning recommendation and decision support systems.

You will gain 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.

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 without being explicitly programmed.

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. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus 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.

There has been an explosion in data, much of which is not fully structured, but contains valuable information such as search trends, consumer behaviour and other patterns. This module aims to cover some of the developments in the broad range of "Big Data" problems. It will give you a good understanding of data structures, software development procedures and the range of analytical tool used to undertake a wide range of standard and custom analyses to provide data solutions to these issues. 

The module aims to introduce managerial approaches to information security in modern enterprises. It considers how to manage the use of information assets securely and support the goals and objectives of enterprises through effective information security governance, risk management, and contingency planning.