BSc (Hons)Computer Science

Core modules

Fundamentals of Computing and Programming

This module provides the essential foundations of computing and programming for students entering software engineering and computer science. Through practice‑led activities such as live coding, pair programming, debugging labs, and guided exercises, you'll be introduced to how computers are structured and operate, how data is represented and processed, and how programs are designed, implemented and tested using a modern programming language.

AI Fundamentals and Professional Practice

This module provides an introduction to artificial intelligence alongside the core professional practices required for success in modern computing disciplines. You'll develop foundational AI literacy by exploring classical AI methods, intelligent agents, search strategies, data fundamentals and introductory machine-learning concepts. Through hands-on exploration of datasets, notebook-based activities and conceptual modelling tasks, you'll gain an applied understanding of how AI systems operate, where they are effective and what limitations or risks they present.

Computer Networks and Security

This module provides a practical introduction to computer networking and security, equipping you with the skills to design, configure, and secure networked systems. Emphasising real-world applications, what you learn in this module supports careers in IT, cybersecurity, and other sectors reliant on secure digital infrastructure.

Web Development and Databases

This module introduces web development and relational data management, equipping you with the essential technical foundations required for building interactive, data‑driven digital systems. It brings together client‑side web technologies, server‑side data persistence, and core database design principles to create fully functional web applications and build the foundation for year two modules.

Core modules

Applied AI and Machine Learning

This module introduces the core principles and practical applications of applied artificial intelligence and machine learning. You'll begin by exploring descriptive data analysis and exploratory data analysis (EDA) techniques to examine datasets, identify patterns, and prepare data for machine learning tasks. You'll then examine key machine learning approaches, including supervised learning methods such as regression and classification, and unsupervised learning techniques including clustering and dimensionality reduction.

Object-Oriented Design and Development

Following the introduction in year one, this module takes a wider-ranging and deeper look at object-oriented software development. Focusing on the full software development lifecycle, you will cover analysis, design, implementation and testing using an appropriate object-oriented language for an appropriate platform. You'll be expected to have prior experience in basic object oriented programming, either from previous study or elsewhere.

Advanced Web Development and Databases

From classic websites to back-ends for mobile apps, the web is all-pervasive these days, and web development skills are in high demand. Web applications are typically backed by databases, and database design and development skills are also vital in web development. This module provides you with the database and web development skills necessary to build such applications. You are expected to have basic web development skills to study this module, i.e. HTML, CSS, and basic JavaScript or TypeScript, from either previous study or elsewhere.

Data Analytics and Visualisation

This module will equip you with the technical and analytical skills required to transform raw data into actionable business intelligence. You'll address the growing industry demand for professionals who can analyse complex datasets using both statistical frameworks and computational tools and will move beyond static data viewing to a practice-led exploration of the analytics lifecycle, learning how to interpret results and justify analytical decisions within professional enterprise contexts.

Core modules

Advanced Data Science and Deep Learning

This module provides a comprehensive exploration of modern data-driven intelligence, balancing the rigorous statistical foundations of advanced data science with the transformative power of deep learning. Designed for the final year of study, it shifts focus from basic implementation to the critical evaluation and synthesis of complex data pipelines and neural architectures. You will engage in intensive, practice-led learning to solve non-linear, real-world problems, ensuring you graduate as a 'creator of knowledge and critical solutions'.

Industrial Consulting and Entrepreneurship

In this module you'll gain practical experience working with employers, industry speakers, entrepreneurs, and external organisations. You will collaborate in development teams on an industry‑set brief, applying digital and technology skills while developing project management, communication, and professional behaviours. Alongside consulting practice, you will explore entrepreneurial thinking by identifying opportunities, generating innovative solutions, and understanding how value is created within technical and digital contexts.

Final Major Project

In this module you will manage your own project, from choosing a topic to producing the final report. You set aims and objectives, keep a project plan, and maintain documentation that records your research and development work. You'll be assigned a supervisor to guide the process, confirm the project scope, and approve ethical requirements.

Optional modules

Please note: Not all optional modules are guaranteed to run each year.

Cloud, IoT and Emerging Technologies

In this module you'll gain advanced, industry aligned knowledge across cloud computing, Internet of Things (IoT), edge systems and next generation emerging technologies. You will learn how to design, deploy and integrate cloud native architectures with IoT devices, edge intelligence, real time data pipelines, and technologies such as 5G, blockchain, digital twins, extended reality (XR), robotics, and autonomous systems.

Generative AI and NLP

This module introduces the core principles and practical applications of natural language processing and generative artificial intelligence. You'll begin by exploring text preprocessing techniques to clean and prepare language data for analysis before examining core NLP techniques, including tokenisation and vectorisation, alongside classical models for text analysis and pattern extraction. Building on this foundation, you'll then explore generative AI concepts, working with large language models to produce and analyse text outputs.

Cloud Security and Automation

This module provides an advanced examination of cloud‑native engineering, with a particular focus on the integration of automated deployment and secure architectural design. As organisations continue to adopt distributed and virtualised environments, the ability to engineer resilient, self‑healing systems becomes essential. You will develop the capability to design and deploy cloud infrastructures using Infrastructure‑as‑Code (IaC), automated CI/CD pipelines, and industry‑standard orchestration platforms.

AI and Autonomous Systems

This module provides an advanced exploration of artificial intelligence and autonomous systems, focusing on the design, evaluation and responsible deployment of intelligent agents operating in dynamic environments. You will develop the ability to engineer AI‑driven behaviours, integrate perception and decision‑making pipelines, and evaluate the safety, reliability and ethical implications of autonomous technologies.