BSc (Hons) Computer Science

• Year 1

• In your first year, you’ll engage with the foundations of computer science from programming to algorithms and mathematics. We’ve structured the curriculum to accurately reflect the industry and its many areas of specialisation. You’ll study programming techniques, database development, how to capture requirements and what happens inside a computing operating system. A hands-on course from the outset, you’ll benefit from a number of practical workshops as well as preparing for your third year work placement.

  Core modules

  • Stage 1 Computing Placement Preparation (BPIE111)

    This module is aimed at students who may be undertaking an industrial placement in the third year of their programme. It is designed to assist students in their search for a placement and in their preparation for the placement itself.

  • Software Engineering 1 (COMP1000)

    This module exposes students to the principles of software design and construction. The basics of constructing source code to solve a problem will be introduced, exposing students to common control structures alongside concepts such as types and generics. Major programming paradigms such as object orientation and functional programming are introduced. Additionally, key software development tools and methods are explored.

  • Computer Systems (COMP1001)

    This module provides students with an underpinning knowledge of how computers work. Topics include low-level systems and representation of data, operating systems, and an introduction to subjects such as virtualisation, parallelism, state and communications. Students will learn how operating systems manage processes and scheduling, and how memory management works.

  • Cyber Security & Networks (COMP1002)

    Modern computing relies upon networking and robust cyber security. This module provides an appreciation of their core enabling technologies, discussing how they can be applied. Key networking topics include routing and switching, as well as wireless networks. Key areas of security include underlying concepts and threats, and exploring security technologies that can be applied to enable defence in depth.

  • Algorithms, Data Structures and Mathematics (COMP1003)

    Data structures and algorithms lie at the heart of Computer Science as they are the basis for an efficient solution of programming tasks. In this module, students will study core algorithms and data structures, as well as being given an introduction to algorithm analysis and basic Mathematics for Computer Science.

  • Computing Practice (COMP1004)

    This module applies problem-based learning to provide students with the ability to identify problems and derive appropriate and considered solutions. A focus will be given to the early stages of the software development lifecycle to develop the skills of eliciting requirements whilst considering operational and technical trade-offs. The module will culminate in the creation of a simple yet complete software solution.

• Year 2

• In the second year, you’ll build on the knowledge you’ve already acquired, engaging with new subjects that will help you identify possible career paths. Students will explore artificial intelligence and machine learning. You will learn how to navigate different processor architectures with low level programming for IoT devices. An integrating project combines all the skills you have learnt so far, and allows you to undergo a full software lifecycle, starting with a concept and ending with a product.

  Core modules

  • Stage 2 Computing Placement Preparation (BPIE211)

    This module is aimed at students who may be undertaking an industrial placement in the third year of their programme. It is designed build on the Level 1 module (BPIE111) and to assist students in their search for a placement and in their preparation for the placement itself.

  • Software Engineering 2 (COMP2000)

    Students’ understanding of software engineering is expanded by introducing a range of topics that instil best practice. Students will learn how to implement faster software using parallelism and consider aspects of human-computer interaction. Object-orientation and functional programming are revisited, while event-driven programming is introduced. Common design patterns used in the construction of software are introduced.

  • Information Management & Retrieval (COMP2001)

    This module introduces students to the fundamental concepts for graphical representation, information management, database systems and data modelling. The capture, digitisation, representation, organisation, transformation and presentation of information is explored using conceptual and physical data models.

  • Artificial Intelligence (COMP2002)

    This module provides students with an introduction to the principles of artificial intelligence and the methods used in that field. Topics covered include search and optimisation, knowledge representation and reasoning, and machine learning. Students will gain experience of modelling and simulation, and will apply analytical tools to evaluating results, and will consider the ethical implications of the introduction of AI.

  • Computing Group Project (COMP2003)

    Knowledge gained in earlier stages of the computing programmes is consolidated and integrated into a substantial project. Students work in teams, champion professional roles, design and develop a software solution for a given scenario. The project integrates and expands upon software development stages covered on the course (project management, analysis, design, construction, communication, security and/or networking).

  • Embedded Programming and the Internet of Things (COMP2008)

    Learn about embedded microcontrollers, work with different processor architectures and develop embedded software. The use of hardware peripherals, interrupts, multi-tasking and defensive programming will be explored and students will use programming strategies to optimize the execution time, energy consumption and memory size of their programs. The use of embedded programming within IoT applications is considered.

• Optional placement year

• This year you’ll do your industry placement – which you’ve been preparing for over the past two years – aided by our network of industry contacts. This extensive training period allows you to learn within a professional context, giving you the opportunity to apply your knowledge and skills in the real world, as well as learning from those around you. Over 48 weeks you’ll gain experience and confidence, as well as a host of contacts – all essential in readying you for employment on graduation.

  Core modules

  • Computing Related Placement (Generic) (BPIE330)

    A 48-week period of professional training spent as the third year of a sandwich course, undertaking an approved placement with a suitable company. This provides an opportunity for you to gain relevant industrial experience to consolidate the first two years of study and to prepare for the final year and employment after graduation. Please note this placement is optional but strongly recommended.

• Final year

• You’ll now be ready to demonstrate all that you’ve learned over the past three years by undertaking a substantial problem-solving individual project focused on a specific area of personal interest, or one that relates to your intended career. Students will explore computational problem solving with GP-GPUs and expand upon machine learning knowledge to analyse real datasets and control real-time systems. Cloud computing is examined to understand the deployment and performance of Internet services.

  Core modules

  • Computing Project (COMP3000)

    The Computing Project provides an opportunity to tackle a major computing related problem in an approved topic area relevant to the programme of study.

  Optional modules

  • Parallel Computing (COMP3001)

    This module develops an understanding of problems in Computer Science which take advantage of general-purpose computing on GPUs. It provides practical methodologies to reformulate problems in terms of hardware architecture, graphics primitives and high-performance computing concepts, as supported by the most recent GPUs. It develops the skills to implement parallel solutions with common GP-GPU computing languages.

  • Alternative Paradigms (COMP3002)

    Imperative programming and related “classic” machines like finite state or Turing machines dominate the field of computing. This module aims to expose students to ways of thinking about computational problems that go beyond mainstream imperative styles (e.g., functional and declarative programming) and to ideas and workings of and behind unconventional and upcoming computing paradigms (e.g. quantum or neural computing).

  • Machine Learning (COMP3003)

    This module introduces machine learning, covering unsupervised, supervised and reinforcement learning from a Bayesian perspective. This includes theory behind a range of learning techniques and how to apply these representations of data in systems that make decisions and predictions.

  • Advanced Computing and Networking Infrastructures (COMP3004)

    This module introduces the infrastructures of the future Internet and cloud, both moving towards virtualisation and softwarisation, and describes how they underpin the development and deployment of multimedia Internet applications and services. Topics include virtualisation and cloud; services and applications; Software Defined Networking, and Network Function Virtualisation; load balancing, performance and resilience.

  • Full-Stack Development (COMP3006)

    This module explores the production of dynamic web applications with a particular focus on the web environment. Key elements such as object oriented and event-based development, asynchronous client-server communication and distributed content representation are explored through practical production. The production of a working system uses dynamic web frameworks such as HTML, CSS and JavaScript/jQuery.

  • HCI, Usability and Visualization (COMP3007)

    This module has three main objectives. The first objective is to enhance the students understanding of the topic of Human Computer Interaction (HCI). The second is to emphasise the crucial role of user feedback in the software development life cycle. The final objective is to exemplify this grounding in HCI and usability evaluation using the application area of Information Visualization.

  • Big Data Analytics (COMP3008)

    The key objective of this module is to familiarise the students with the most important information technologies used in manipulating, storing and analysing big data. Students will work with semi-structured datasets and choose appropriate storage structures for them. A representative of recent non-relational trends is presented—namely, graph-oriented databases.

  • Security Operations & Incident Management (COMP3010)

    This module will examine the incident management and the role it plays within modern information security systems. It will introduce key concepts in the analysis of network traffic for signs of intrusions, as well as the process of responding to computer incidents including the identification and analysis of malicious code.

  • Ethical Hacking (COMP3011)

    Understanding the security and vulnerabilities of IT systems is critical in their protection. This module seeks to develop the knowledge and skills to undertake penetration testing of systems. A range of passive and active offensive techniques will be taught, alongside an in-depth understanding of the legal and ethical issues surrounding such activity.

  • Digital Forensics & Malware Analysis (COMP3012)

    This module examines the procedures, tools and techniques utilised within the field of digital forensics. It will introduce an understanding of the methodology deployed in the handling of digital evidence, the volatility of data and maintaining the integrity of data. Knowledge and skills will be developed of tools and techniques to examine and analyse forensic data across differing computing platforms.

  • Games Graphics Pipelines (COMP3015)

    This module develops core programming skills for game developers, targeting specific elements of graphics pipelines; rendering, shading and optimisation for varied platforms such as AR (mobile) VR and XR platforms. The module focuses on specific skills required to develop tools/solution for emerging game technologies.

  • Immersive Game Technologies (COMP3016)

    This module introduces the concepts and programming techniques for high performance real-time graphics using a relevant graphical API. A bottom-up view of graphical programming is taken, excluding the use of game engines and high-level prototyping tools. Students also learn transferrable skills: programming in an un-managed environment, tools programming, programming for physical interfaces and/or sensors.

  • Computing Project Management (COMP3017)

    This module provides the opportunity for students to acquire a critical understanding of the management and methodological issues associated with Software Development. 

Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

The following programme specification represents the latest course structure and may be subject to change:

BSc Computer Science programme specification 3429

UCAS tariff

120 - 128