The modules we offer are inspired by the research interests of our staff and as a result, may change from year to year. The following list is therefore subject to change but should give you a flavour of the modules we offer.
Programming and Algorithms
Systems and Architecture
Mathematics for Computer Scientists
You’ll cover the basic concepts in mathematics which are of relevance to the computer scientists. Topics which will be covered include: logic; sets, functions and relations; graphs; induction, basic probability and statistics; matrices. You’ll spend around four hours per week in lectures and tutorials for this module.
Database and Interfaces
Fundamentals of Artificial Intelligence
Algorithm Correctness and Efficiency
Software Engineering Group Project
Working in groups of around five to six people, you’ll be assigned a supervisor who will provide you with a short written description of a computer application to be designed, programmed, and documented during the course of the module. Each group will meet twice a week, once with your supervisor and once without; you’ll also have four introductory one hour lectures.
Graphical User Interfaces
This module will introduce you to programming concepts and structures by considering the Java Swing packages in depth. You’ll explore a wide range of components, and will consider the other APIs, which allows easy incorporation of high-quality 2D graphics, text, and images in applications, and the use of Integrated Development Environments (IDEs), which simplify the construction of graphical user interfaces. You’ll spend around four hours each week in lectures and computer classes.
Computer Communications and Networks
This module will give you an overview of technologies including data transmission techniques, Local Area Networks, Wide Area Networks, network security, and network applications. You’ll pay particular attention to the internet environment and TCP/IP protocols. You’ll spend around two hours each week in lectures for this module.
Artificial Intelligence Methods
Introduction to Image Processing
Topics in Computer Science
Human Computer Interaction
Through two hours of lectures each week, you’ll be given an overview of the field of Human Computer Interaction, which aims to understand people's interaction with technology and to apply this knowledge in the design of usable interactive computer systems. The module will introduce the concept of usability and will examine different design approaches and evaluation methods.
Languages and Representations
Planning. Search and Artificial Intelligence Programming
You’ll be introduced to Artificial Intelligence (AI) algorithms and programming techniques for search and planning. Topics covered include: classical search; search with non-determinism and partial observability; local search; classical planning; reasoning about actions; planning under uncertainty; conditional planning; planning with time and resources; other typical AI problems and how to implement them in an AI programming language.
Operating Systems Distributed/Parallel
You will cover the programming material and concepts necessary to obtain an understanding of the C++ programming language. You will spend around four hours per week in lectures and computer classes for this module and will be expected to take additional time to practice and to produce your coursework.
Individual Dissertation Software Engineering
You’ll perform an individual project on a topic in computer science with emphasis software systems. You’ll produce a 15-25,000 word project report under the guidance of your supervisor, who you will meet with for an hour each week. The topic can be any area of the subject which is of mutual interest to both the student and supervisor but should involve a substantial software development component.
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You’ll begin by considering the attempts to characterise the problems that can theoretically be solved by physically-possible computational processes. You’ll then consider the area of complexity theory, looking at whether or not problems can be solved under limitations on resources such as time or space. A key topic is an examination of the classes P and NP and the definition of the term NP-complete. You’ll spend around two hours a week in lectures for this module.
Automated Decision Support
The main aim of this module is to provide a sound understanding of wide range of fundamental concepts, techniques and methods of Operational Research and Artificial Intelligence that can help in design of automated intelligent decision support systems. The module will present a variety of applications from industrial and service sectors.
Spending four hours a week in lectures and computer classes, you’ll cover the following topics: security of the computer; security of networks; security and the internet; software and hardware security; mobile security; and basic cryptography.
Knowledge Representation and Reasoning
This module examines how knowledge can be represented symbolically and how it can be manipulated in an automated way by reasoning programs. Some of the topics you’ll cover include: first order logic; resolution; description logic; default reasoning; rule-based systems; belief networks and fuzzy logic. You’ll have two hours of lectures each week for this module.
New Media Design
This is a practical module covering the critical elements of New Media Design, with a particular focus on its use in the web. Critical elements such as colour, images, audio, video and animation will be introduced and discussed, in addition to broader issues around usability and interaction. Processes to support effective design work will also be considered. You’ll gain hands-on experience of technologies used to manipulate New Media in a professional context. Such tools will be put into context with emerging paradigms, including new media for mobile platforms.
Collaboration and Communication Technologies
In this module you’ll consider the design of collaboration and communication technologies used in a variety of different contexts including workplace, domestic and leisure environments. You’ll consider the basic principles of such technologies, explore the technologies from a social perspective, consider their impact on human behaviour and critically reflect on their design from a human-centred perspective. You’ll spend around two hours per week in lectures for this module.
You’ll examine the principles of 3D computer graphics, focusing on modelling the 3D world on the computer, projecting onto 2D display and rendering 2D display to give it realism. Through two hours weekly of lectures and laboratory sessions, you’ll explore various methods and requirements in 3D computer graphics, balancing efficiency and realism.
Fuzzy Sets and Fuzzy Logic Systems
You’ll review classical Boolean logica and set theory, including the common operations of union, intersection and complement. Fuzzy Logic Systems (FLSs) will be introduced and illustrated in conjunction to examples of real world applications in industrial control and other areas. You’ll spend around four hours each week in lectures and workshops, and will be given the opportunity to design, programme and deploy a fuzzy logic system, providing a tangible real world example of some underlying concepts of FLSs.
Autonomous Robotic Systems
This module introduces you to the computer science of robotics, giving you an understanding of the hardware and software principles appropriate for control and localisation of autonomous mobile robots. A significant part of the module is laboratory-based, utilising physical robotic hardware to reinforce the theoretical principles covered. Spending around three to four hours each week in lectures and practicals, you’ll cover a range of topics including basic behavioural control architectures, programming of multiple behaviours, capabilities and limitations of sensors and actuators and filtering techniques for robot localisation.
Providing you with an introduction to machine learning, pattern recognition, and data mining techniques, this module will enable you to consider both systems which are able to develop their own rules from trial-and-error experience to solve problems as well as systems that find patterns in data without any supervision. In the latter case, data mining techniques will make generation of new knowledge possible, including very big data sets. This is now fashionable termed 'big data' science. You’ll cover a range of topics including: machine learning foundations; pattern recognition foundations; artificial neural networks; deep learning; applications of machine learning; data mining techniques and evaluating hypotheses. You’ll spend around six hours each week in lectures and computer classes for this module.