The following is a sample of the typical modules that we offer as at the date of publication but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Due to the passage of time between commencement of the course and subsequent years of the course, modules may change due to developments in the curriculum and the module information in this prospectus is provided for indicative purposes only.
Programming and Algorithms
The module introduces basic principles of programming and algorithms. It covers fundamental programming constructs, such as types and variables, expressions, control structures, and functions. You'll learn how to design and analyse simple algorithms and data structures that allow efficient storage and manipulation of data. You'll also become familiar with basic software development methodology. You will spend around six hours per week in lectures, computer classes and tutorials.
You will gain a basic understanding of the fundamental architecture of computers and computer networks. You’ll learn how the simple building blocks of digital logic can be put together in different ways to build an entire computer. You’ll also learn how modern computer systems and networks are constructed of hierarchical layers of functionality which build on and abstract the layers below. You will spend five hours per week in tutorials, lectures and computer classes.
Systems and Architecture
This module runs alongside 'Computer Fundamentals' and provides an expanded view by considering how real computer systems (such as ARM, x86, Linux and *BSD) and networks work. You’ll also cover the principles of the lower level implementation of I/O using polling and interrupts, and the use of exceptions; how memory and storage is organized as well addressing the issues arising from multicore systems. You’ll spend around five hours per week in tutorials, lectures and computer classes.
Mathematics for Computer Scientists
You’ll cover the basic concepts in mathematics which are of relevance to the computer scientists. These include: logic; sets, functions and relations; graphs; induction, basic probability and statistics and matrices. You’ll spend around four hours per week in lectures and tutorials.
Database and Interfaces
This module considers both the structure of databases, including how to make them fast, efficient and reliable, and the appropriate user interfaces which will make them easy to interact with for users. You will start by looking at how to design a database, gaining an understanding of the standard features that management systems provide and how you can best utilise them, then develop an interactive application to access your database.
Throughout the lectures and computing sessions you will learn how to design and implement systems using a standard database management system, web technologies and GUI interfaces through practical programming/system examples.
Introduction to Software Engineering
You will focus on the fact that programming is only one step of the larger software engineering process. To develop good software, you must gather requirements, design it well, plan the development, do the programming, have a testing strategy, test the parts and the product as a whole, and have a maintenance strategy after it was delivered.
You will spend around two-three hours per week discussing the stages in lectures, whilst carrying out activities in labs that help you understand the underlying issues.
In this module you will learn the basic principles of the object-oriented and functional approaches to programming, using the languages Java and Haskell. You will also see how they can be used in practice to write a range of different kinds of programs. You will spend around five hours per week in lectures and labs for this module.
Fundamentals of Artificial Intelligence
You will gain a broad overview of the fundamental theories and techniques of artificial intelligence (AI). You’ll explore how computers can produce intelligent behaviour, and will consider topics such as the history of AI, AI search techniques, neural networks, data mining, philosophical and ethical issues, and knowledge representation and reasoning. You will spend two hours per week in lectures.
Algorithms and Data Structures
This module introduces you to the basics of how to specify abstract data types and use them to design programs. You’ll cover the use of mathematical descriptions of the computational resources needed to support algorithm design decisions. The emphasis is upon understanding data structures and algorithms so as to be able to select them appropriately for solving a given problem. You’ll spend around three hours per week in lectures and computer classes.
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.
Operating Systems and Concurrency
This course covers the fundamental principles that underpin operating systems and concurrency. Topics covered include the architecture of operating systems, process and memory management, storage, I/O, and virtualisation. The principles of concurrency will be introduced from both the perspective of an operating system and user applications. Specific topics on concurrency include: hardware support for concurrency; mutual exclusion and condition synchronisation; monitors; safety and liveness properties of concurrent algorithms, and the use of threads and synchronisation.
Machines and their Languages
You’ll investigate classes of formal language and the practical uses of this theory, applying this to a series of abstract machines. You’ll focus in particular on language recognition, but will study a range of topics including: finite state machines; regular expressions; context-free grammars; and Turing machines. You’ll spend around two hours per week in lectures.
Software Application Development
This module builds on your basic Java programming developed in year one. Topics include: design diagrams and modelling; GUI programming; testing; software engineering methodologies (including agile development) in the context of understanding and refactoring other people's code. You will spend around two hours per week in lectures and two hours per week in computer classes.
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.
Advanced Functional Programming
Building upon the introductory Functional Programming module in year one, you’ll focus on a number of more advanced topics such as: programming with effects; reasoning about programs; control flow; advanced libraries; improving efficiency; type systems; and functional pearls. You’ll spend around four hours per week in lectures and computer classes.
Introduction to Formal Reasoning
Developing the themes of the year one module Mathematics for Computer Scientists, you’ll be introduced to a mathematically rigorous approach to program construction. You’ll study topics such as: proofs in propositional logic and predicate logic; classical vs. intuitionistic reasoning; basic operations on types; verification of list based programs; and introduction to program specification and program correctness. You’ll spend around five hours per week in lectures, tutorials and computer classes.
Introduction to Image Processing
This module introduces the field of digital image processing, a fundamental component of digital photography, television, computer graphics and computer vision. You’ll cover topics including: image processing and its applications; fundamentals of digital images; digital image processing theory and practice; and applications of image processing. You’ll spend around three hours in lectures and computer classes each week.
Planning and Search
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.
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 and will be expected to take additional time to practice and to produce your coursework.
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.
Individual Dissertation Single Honours
Through a one hour lecture and a tutorial with your supervisor each week, you’ll develop your own independent research project and written report. Topics can range from purely theoretical studies to practical work building a system for a third party.
Computers in the World
The module looks broadly into the impact that computer systems have in society and the implications of this from the perspective of a computer scientist, while considering a range of legal, ethical, professional and social issues. The module covers topics such as ethics, critical thinking, professionalism, privacy, intellectual and intangible property, cyber-behaviour, accountability, safety, dependability and reliability, all within the context of computer systems development. You will spend one hour per week in lectures and one hour per week in group-based workshops for this module.
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 per week in lectures.
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.
Software Quality Management
Through a two hour lecture each week, you’ll be introduced to concepts and techniques for software testing and will be given an insight into the use of artificial and computational intelligence for automated software testing. You’ll also review recent industry trends on software quality assurance and testing.
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. 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.
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.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.
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.
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 per week of lectures and laboratory sessions, you’ll explore various methods and requirements in 3D computer graphics, balancing efficiency and realism.
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.
Fuzzy Sets and Fuzzy Logic Systems
You’ll review classical Boolean logic 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.
Students taking part in activities relating to programming experience such as developing apps in their spare time, contributing to open source projects, or building things in hackathons may receive academic credit for showing they have experience and excellent development skills. The emphasis of this module is that you provide evidence of your significant extra-curricular software development experience. Students will only be able to register for this module with the approval of the convenor/school, once the material for assessment has been checked.
Students taking part in activities relating to industrial experience in a computer science or software engineering enterprise may obtain academic credit for them. A full list of approved activities is available from the School Office. Activities will be related to demonstration of involvement in development of complex software in a team situation, subject to quality control procedures of an industrial or business practice. Evidence of working to and completing tasks relating to targets set by an employer and directly related to software development/programming will be required. Students will have undertaken an agreed number of hours on the activities, identified personal goals and targets in relation to these activities and maintained a reflective portfolio as a record of evidence of their competence and achievements. The nature of the activities undertaken will be subject to the approval of the module convenor before acceptance on the module.
Students taking part in approved activities, such as running code clubs in schools, organising school computing activity days, or becoming active STEM ambassadors, may receive academic credit for demonstrating they have actively contributed to the development of younger students. Students will have undertaken an agreed number of hours on the activities, identified personal goals and targets in relation to these activities and maintained a reflective portfolio as a record of evidence of their competence and achievements. Students will only be able to register for this module with the approval of the convenor/school, once the material for assessment has been discussed.