Computer Science MComp

Core modules:

Introduction to Software Engineering

This module will introduce students to the principles of software engineering, discussing the software lifecycle and approaches to effective teamwork. Students will be introduced to a development framework, which they will work on individually, and then will apply the principles of software engineering, working in a team to develop a software project.

20 credits

Foundations of Computer Science

In the first semester of this module, we will cover the topics in discrete mathematics that provide an essential foundation for later studies in the school. This includes topics such as sets, functions, and relations, propositional and predicate logic, boolean algebra, combinatorics, induction, recursion, proof strategies, graph theory, and number theory. In the second semester of this module, we will cover the topics in continuous mathematics that provide an essential foundation for later studies in the school. This includes topics such as trigonometric, exponential and logarithmic functions, polynomials, limits and continuity, differential calculus of one and two variables, integration, series summation and power series, matrices, vector calculus and linear algebra.

20 credits

Java Programming

This module is about programming in the Java language. There is no requirement that students arrive with any knowledge of programming although many do and some are already very experienced programmers. This module is intended to ensure that both absolute beginners and strong programmers are capable of writing clear, well structured, readable programs in Java by the end of the module. The module is largely taught through practical classes but students will have the opportunity to pace their own learning based on their prior experience. It does mean that beginners will have to work harder than students who arrive as experts, though some students who consider themselves to be experts may have some unlearning to do

20 credits

Systems and Networks

In this module, we investigate topics surrounding the function and operation of modern devices, from the foundations of digital logic and number systems to an overview of operating systems and their function and the different types of computer networks and associated protocols (including IP addressing, ethernet fundamentals, switching technologies, router operations supporting small-to-medium business networks, wireless local area networks (WLAN), and key security concepts).

20 credits

Practical Algorithms and Data Structures

This module will reinforce the programming concepts that were taught in the autumn semester's programming module while exploring essential data structures and algorithms. This includes a particular focus on algorithms used in traditional AI. Students will also learn to analyse the efficiency of algorithms and data structures, and make informed choices about these for practical problems.

20 credits

Introduction to Artificial Intelligence and First Year Reflection

This module will explore intelligence, what it is, how we might measure it, and how we can learn from natural intelligence, in humans and animals, to create new forms of artificial intelligence (AI) for machines.  A key theme will be to examine similarities and differences between brains and computers, and particularly, the idea that both are able to act intelligently by performing computation. Through lectures, seminars and computer-based lab classes, the module will investigate some of the key computational building blocks of intelligent systems, including perception and reasoning, as found in nature and explored through AI. The module will also explore some of the real-world, societal and ethical implications of recent developments in AI and robotics. Alongside this introduction to artificial intelligence, a parallel thread will support the development of academic and professional skills including the appropriate and ethical use of AI in scholarship and in the workplace. This stream will start with a focused, week-long, cross-faculty interdisciplinary design activity aimed at equipping students with essential teamwork, design, problem-solving, and communication skills. Particular attention is paid to employability, sustainability, and inclusivity. Through real-life engineering projects, students are introduced to tackling complex challenges. Throughout semester, students will reflect upon the content of first year, the skills that have been developed, and their relevance to future study and careers. This includes consideration of why the School believes every one of our undergraduate students should have solid foundations in artificial intelligence, software engineering and the theoretical underpinnings of Computer Science.

20 credits

Core modules:

Programming Language Principles

On entering this module you will already have a good understanding of object oriented programming from your first year studies. In this module, you will be introduced to further paradigms and programming languages. You will explore the choices that are taken in language design and the relationship between high level language and machine-level code that can be directly executed. In this module you will also look at the particular issues associated with concurrent or parallel programming, and the techniques used to combat them.

20 credits

Databases and Logic in Computer Science

This module introduces the foundations of databases and logic in computer science. You will cover theoretical underpinnings including the syntax and semantics of propositional and predicate logics, natural deduction, notions such as soundness, completeness and (un)decidability, normalisation theory of databases, relational algebra and relational calculus. You will also study practical applications of both databases and logic. This will include the use of SQL, including from within other programming languages, and practical applications of formal logic, such as automated reasoning and procedures, and the use of logic for formal verification of computer systems).

20 credits

Automata, Computation and Complexity

This module introduces the theoretical foundations for computing systems: finite state machines, pushdown automata, and Turing machines, along with the formal languages that can be recognised by these machine models.

It also deals with the question 'What is computable?' and 'What is efficiently computable?' by showing when problems are computationally hard, and how to find algorithmic solutions to computationally hard problems.

20 credits

Foundations and Applications of Artificial Intelligence

This module will provide the mathematical and statistical underpinnings for artificial intelligence, some of which are used more widely in computer science, and look at some practical applications of AI, with a focus on data science.

Semester 1 will focus on the mathematical and statistical underpinnings, including probability, random variables and distributions (both discrete and continuous), finite sample spaces, Bayes rule, sampling, hypothesis testing, the law of large numbers, the central limit theorem and linear regression.

Semester 2 will provide an introduction to practical data science. Topics include: data preprocessing, feature extraction, feature selection, and supervised/unsupervised learning. The module will employ a practical Python-based approach to help students develop an intuitive grasp of the sophisticated mathematical ideas that underpin this challenging but fascinating subject.

20 credits

- Software Hut (20 credits)
The Software Hut (a microcosm of a real Software House) gives students an opportunity to experience the processes of engineering a real software system for a real client in a competitive environment. The taught element covers the tools and technologies needed to manage software development projects successfully and to deliver software products that meet both client expectations and quality standards.

Topics that are put into practice include: the requirements engineering process; software modelling and testing; using specific software development framework(s); group project management; quality assurance; testing. Tutorials take the form of project meetings, and so are concerned with team management, conduct of meetings and action minutes.

Before the software engineering exercise commences, a focused, week-long, cross-faculty interdisciplinary design activity will take place, aimed at equipping students with essential teamwork, design, problem-solving, and communication skills. In addition to a focus on employability, sustainability, and inclusivity, students apply more advanced engineering technical knowledge to industry-relevant, complex, and interdisciplinary problems.

- Cybersecurity in Action and Professional Issues (20 credits)
This module has two components. In the first, it aims to teach students about the key security features needed in today's computer systems, how these features can be attacked, and the ways to prevent such attacks. It covers security in a variety of settings, focusing on important topics that are usually taught in the first two years of Computer Science courses, but also looks at some unique aspects of security.

We use a practical, hands-on approach to learning about security, similar to what's known as 'Capture the Flag' (CTF) exercises. The goal is to develop not only technically proficient but also ethically responsible professionals, who are aware of the consequences of their actions on individuals, organisations, and society at large, thereby preparing them to be conscientious and ethical leaders in the cybersecurity field.

The second component looks more widely at the professional issues in the computing discipline, particularly the commercial context and relevant legal matters.

Core modules:

Dissertation Project

In the individual research project, you will complete a major original piece of software design, or an experimental investigation. This work will be reported formally in a research dissertation and also presented at a project presentation session, to which industrial representatives, students and academics are invited. The work will include an Interim report that consists of an initial survey and literature review. You will be engaged in a major piece of software development, or the design and execution of an empirical experiment. You will have regular meetings with your supervisor, who will advise on any problems you encounter. You will prepare an 7,000-14,000 word dissertation, which includes the material from the interim report, but also contains a complete design, implementation and evaluation of the results of your project. This may be assessed by oral examination. 

40 credits

Optional modules:

Introduction to Speech and Audio Processing

This module introduces computer-based approaches to analysing one of the most important human phenomena - speech. It explores both speech production and perception, and in doing so it takes a multi-disciplinary perspective that draws on engineering, linguistics, and cognitive science. Students are introduced to  digital signal processing as a core methodology for extracting information carried by the speech signal, and statistical modelling as a primary instrument for making robust inferences. You will learn how speech is captured, represented, and processed in digital form, and how speech signals can be analysed and applied in real-world AI technologies. By the end of the module, you will have developed practical skills in speech analysis and a deeper understanding of how speech technologies underpin modern human-computer interaction, particularly in a world increasingly shaped by AI.

20 credits

3D Computer Graphics and Image Processing

This module begins with the mathematical foundations of image processing, covering the techniques used to restore, enhance, and extract data from digital imagery, which are essential to computer vision and medical imaging. These techniques are also relevant in 3D graphics for tasks such as surface texturing and cinematic post-processing. The module then continues with a focus on 3D computer graphics dealing with the fundamental concepts that are the basis of work in a range of industries, such as entertainment (games and film) and computer-aided design (CAD). Both basic and advanced topics concerned with the production of images of 3D objects are covered, including 3D representations and manipulations, light reflection models, realism techniques (such as shadows and textures), ray tracing, and 3D animation.

20 credits

Security and Internet of Things

As the number of Internet-connected devices grows exponentially, understanding the security implications of the Internet of Things (IoT) becomes increasingly critical. This module provides an introduction to the architecture of IoT systems and their unique security challenges, covering topics such as constrained devices, communication protocols, attack surfaces, and security-by-design principles.

Students will explore real-world vulnerabilities and mitigation techniques, including cryptographic solutions, secure boot, trusted execution environments, and secure lifecycle management. Through a combination of lectures, case studies, and hands-on activities, students will develop the skills to evaluate and design secure IoT solutions.

This module is ideal for students interested in cybersecurity, embedded systems, and networked devices, and provides foundational knowledge for careers in connected technologies and cyber risk management.

20 credits

Advanced Algorithms and Programming Semantics

Algorithms and programming languages are at the core of computer science. In the first half of this module, we focus on advanced algorithmic techniques for solving complex computational problems. It covers probabilistic tools, various algorithmic techniques, and a number of modern computational models that deal with massive datasets - these are crucial for students who are aspiring researchers or industry professionals. The second half of this module will focus on a strong theoretical basis for the analysis and design of concurrent systems. We will use the process calculi to model and reason about complex systems, studying both its formal semantics and its many uses, via a number of examples.

The module integrates research-led teaching to introduce students to cutting-edge topics in both algorithm design and concurrency theory. The students gain theoretical as well as practical skills relevant to research and industry demands, making them well-prepared for any career requiring a deep understanding of core topics in theoretical computer science.

20 credits

Advanced Software Engineering

This module aims to advance students' software engineering skills by focusing on specific aspects of the software engineering lifecycle, including (but not limited to) analysis, testing, maintenance, and re-engineering of software systems.

20 credits

Deep Learning

This module provides a rigorous and comprehensive grounding in deep learning and neural networks, spanning mathematical foundations, modern architectures, and selected research frontiers. It introduces students to the building blocks of contemporary deep models, from feed-forward and convolutional networks to recurrent architectures and Transformers, as well as optimisation approaches such as transfer learning and efficient fine-tuning. Students will develop the ability to implement, optimise, and evaluate deep models and their training procedures, while cultivating a critical view of the capabilities, limitations, and trade-offs of common architectures and algorithms. Emphasis is placed on the mathematical formulation and interpretation alongside practical competencies in coding, developing and analysing deep learning approaches. By the end of the module, students will be prepared for professional practice and research, with the knowledge and skills to apply methods appropriately, analyse and report results transparently.

20 credits

Undergraduate Ambassadors Scheme in Computer Science

This module provides an opportunity for students to gain first-hand experience of computer science education through a mentoring scheme with a teacher in a local school. Typically, each student will work with one group for half a day every week, for 10 weeks. Students will be given a range of responsibilities from teaching assistant to the organisation and teaching of self-originated special projects. Only a limited number of places are available and students will be selected on the basis of their commitment and suitability for working in schools. 

This module has no summer resit. Failure in this module will normally require students to repeat it the following year with attendance.

20 credits

Foundations of Natural Language Processing

This module introduces the foundations of Natural Language Processing (NLP), focusing on how natural language text is represented, modelled, and processed computationally. Students will learn core concepts, representations, and modelling approaches that underpin NLP systems, and will gain practical experience implementing text processing and NLP techniques using contemporary programming tools.

20 credits

Mobile Application Development

By studying this module, you will be given the opportunity to gain a thorough grounding in the principles and practice of application design and development for mobile devices.

You will learn and apply topics including mobile design patterns, GUI (Graphical User Interface) design system, software architecture, app lifecycle, reactive framework event/state handling, UI (User Interface) components, sensors, device persistence and cloud services/databases for mobile users.

You will develop a mobile application using a reactive programming framework.  You will learn to build, debug and test on emulated and real devices.  You will also gain general principles that are common across all mobile platforms.

As part of a development team, you will design and develop a substantial, realistic, mobile app, that you will be able to show to employers.

20 credits

Nature-inspired Computation and Modelling

This module focuses on modern artificial intelligence (AI) techniques and their inspiration from natural (primarily biological) systems and conversely, how modelling and simulation techniques can be applied in order to study, simulate and understand the natural world. Students will encounter optimisation algorithms inspired by Darwinian Evolution and biological swarms and neural-inspired data modelling in the form of feed-forward and recurrent neural networks. They will also cover nature-inspired simulation approaches in the form of swarm-inspired agent-based models and tissue-inspired cellular automata, as well as more traditional numerical approaches (differential equations). The bidirectionality of the influence of the natural world on computation and the application of computational methods for modelling and prediction will be emphasised throughout the module.

Teaching will be delivered by lectures, introducing both the key concepts of the natural systems and the relevant algorithmic/mathematical and numerical foundations. A selection of optimisation, modelling and simulation techniques are explored in more depth using Python-based active learning exercises. There is an emphasis on applying the scientific approach to practical work within this module.

20 credits

Cryptography

This module provides an introduction into (post quantum) cryptography and cryptographic protocols focussing on theoretical understanding and practical use of cryptography and cryptographic mechanisms for building secure systems. It aims to develop knowledge and understanding of fundamental principles of information security, the security guarantees of cryptographic primitives, attacks and countermeasures against cryptosystems and provide practical experience of implementing secure systems using cryptographic libraries. The module requires a solid understanding of mathematical concepts (e.g., modulo-arithmetic, discrete mathematics, lattice problems,  probability binary operations), introduces fundamental mathematical concepts needed to understand cryptographic primitives (e.g., group theory and basic complexity theory) and requires a solid understanding of some programming language (e.g., Python, Java or C, but solutions will be given in Python).

20 credits

Robotics

This module is concerned with the design and implementation of the technology underpinning contemporary robotics. The course has a multidisciplinary content spanning psychology, computer science and robotics. 

20 credits

Core modules:

- Turing Research Project (45 credits)
The Turing research project provides the opportunity for students to engage in a substantial piece of collaborative research work. The team component to the research is an essential feature of this module.

Projects are suggested and supervised by staff from the School of Computer Science, in line with their research interests. After students are allocated to projects, teams form, then refine the scope of the research by conducting a thorough analysis of the topic area and formulating a solution with the help of their supervisor. The project is developed under strong supervision and appropriate interim reports are produced and presented.

The project culminates with the production of a publication of the research finding and a full report of the work carried out, as well as a final conference style presentation.

The module is not primarily concerned with software development, although software development may be involved as part of the process of carrying out the research such as constructing the required 'experimental apparatus'.

Self-directed Professional Development

One of the most valuable assets a graduate can possess is the ability to identify and bridge their own competency gaps. This core module supports your transition to early-career graduate life by providing the opportunity to self-reflect on your current skill set and apply the insight gained to enhance your employability by developing a new skill relevant to your planned career.

Students will begin by conducting a gap analysis against their intended career path, then identifying a specific area for improvement and generating an individual learning plan that includes quantifiable objectives. For the majority of the module, each student will focus on developing the skill identified by implementing the learning plan. Finally, students will critically reflect on their experience and assess the effectiveness of their learning.

The module supports students to develop (1) a strong profile as a graduate and (2) a clear sense of how to work towards their next professional goal. 

15 credits

Optional modules:

Cyber Threat Hunting and Digital Forensics

The module provides an in depth view of threat hunting in memory, file system and network data and an introductory analysis of malicious programs. Practical sessions will elaborate on key concepts of incident handling, cyber threat hunting and digital investigation along with detailed analysis of real world case studies. We will also introduce some unusual and non-virulent types of malware.

15 credits

Testing and verification in safety-critical systems

This module provides an introduction to the processes and problems of building complex software such as for use in aerospace applications. Topics covered can be split into four major groups: safety, specification languages, concepts of software engineering, different methods of software testing. A substantial amount of time will be spent on the ideas of software testing and specific testing techniques. 1. Safety includes software and systems safety, methods of performing hazard analysis, human factors and the IEC 61508 standard. 2. Specification languages such as Statecharts. 3. Software engineering concepts focus on the software lifecycle, safe language subsets, software testing and maintenance. 4. The software testing part is concerned with advanced approaches to generating software tests.

15 credits

Cybersecurity Team Project

Cybersecurity Team Project is a module that equips students with the knowledge needed to keep an organisation secure from today's cyber security threats and presents the necessary steps to take when a breach occurs. Using a combination of learning methods and teaching techniques such as project based learning, active learning and case studies, this module teaches cyber security principles and techniques that are needed to secure the digital assets of an organisation. Students on the module will learn about security assessments and testing in today's increasing threat landscape. A major part of this module involves students working in teams to implement, evaluate and develop secure strategies to solve real-world cyber security issues for organisations. This module has the explicit objective of developing group teamwork skills. Participation in teamwork is mandatory and failure on this aspect would require a repeat period of study in a subsequent academic period.

15 credits

Human-Computer Interaction and Visual Analytics

This module offers a comprehensive overview of the fundamental aspects, methodologies, and advancements in the fields of Human-Computer Interaction (HCI) and Visual Analytics. It aims to provide you with the knowledge required to design, develop, and evaluate interfaces and interactive data visualisations that effectively and acceptably meet users' needs. By integrating principles of human perception and cognition with computational data analysis, students will learn to create systems that support complex decision-making and discovery in data-rich environments.

15 credits

Cognitive and Biomimetic Robotics

Cognitive robotics is the field of creating robots that perceive, remember, learn, reason and interact. Biomimetic robotics designs systems using principles discovered in nature, drawing from the evolution and development of natural intelligence in animals, including humans. This module explores progress in these fields, relating advancements in artificial intelligence, machine learning, and cognitive science to the development of next-generation robotic systems. The practical component focuses on modifying and programming biomimetic cognitive architectures, while providing a framework to reflect on the philosophical, societal, and ethical issues relating to robotics research.

15 credits

Parallel Computing with Graphical Processing Units (GPUs)

Accelerator architectures are discrete processing units which supplement a base processor with the objective of providing advanced performance at lower energy cost. Performance is gained by a design which favours a high number of parallel compute cores at the expense of imposing significant software challenges. This module looks at accelerated computing from multi-core central processing units (CPUs) to graphics processing unit (GPU) accelerators with many TFlops of theoretical performance. The module will give insight into how to write high performance code with specific emphasis on GPU programming with NVIDIA CUDA GPUs. A key aspect of the module will be understanding what the implications of program code are on the underlying hardware so that it can be optimised.

15 credits

Development of Secure Software

This module covers the security analysis - as well as the secure development - of software-based systems, both on an architectural as well as a system level. The main goal of this module is to teach the foundations of secure software design, secure programming, and security testing. The module requires a solid understanding of software development in general and in particular, of at least one programming language (e.g., Java, JavaScript, Ruby, C#, F#, or C) and basic software development tools such as an IDE (e.g., Eclipse, VS Code), a revision system (e.g., git), or build systems (e.g., Maven, Gradle, npm, FAKE). Moreover, an understanding of database and Web applications is required. The labs require a basic command of Linux in general and the command line (shell) in particular.

15 credits

Speech Technology

This module introduces the principles of the emergent field of speech technology, studies typical applications of these principles and assesses the state of the art in this area. Students will learn the prevailing techniques of automatic speech recognition (based on statistical modelling); will see how speech synthesis and text-to-speech methods are deployed in spoken language systems; and will discuss the current limitations of such devices. The module will include project work involving the implementation and assessment of a speech technology device.

15 credits

Software and Hardware Verification

This module introduces state-of-the-art software and hardware verification techniques which are widely used in industry. They are particularly important in safety-critical applications, where system failures can not be tolerated. Designing high quality dependable computing systems is widely believed to be the main challenge in computer science. Particular focus is on protocol verification and hardware design verification by model checking and program verification by formalisms such as Hoare logics. These techniques presume formal system specifications and use automated tools for analysing whether a system satisfies the properties required or imposed.

15 credits

Reinforcement Learning

How do machines learn to choose actions when nobody provides the 'correct' answer? In this module you will study how an agent can learn through trial and error by interacting with an environment and receiving rewards. You will develop the core concepts of reinforcement learning from first principles, including decision-making under uncertainty and learning optimal behaviour over time. Throughout the module you will implement key reinforcement learning methods directly, gaining insight into how optimisation and feedback drive learning. You will also engage with state-of-the-art reinforcement learning through guided reading of current research papers, building the skills needed to interpret and critique contemporary work in the field. By the end of the module you will be able to implement and evaluate a range of reinforcement learning algorithms and understand where they are effective, and where they can fail.

15 credits