Overview

Artificial intelligence is changing how machines learn, reason and support decisions, with applications reaching from medical diagnostics to climate modelling and autonomous vehicles. Studying BSc (Hons) Computer Science with Artificial Intelligence at Keele University gives students a firm grounding in computing alongside specialist knowledge of how intelligent systems are designed. The specialism is strongly research focused, introducing computational intelligence and nature-inspired algorithms before moving on to neural networks, evolutionary computation and adaptive behaviour in natural systems. Teaching combines interactive lectures, small-group workshops and practical sessions in computer laboratories, with input from external guest speakers. Core study covers programming, data science, software engineering and machine learning, and the final year centres on an AI research and development project. Placement and international study routes are available for students who want wider experience. The course suits those who want to build, analyse and question intelligent technology, and graduates gain the technical depth and ethical awareness to work in AI, software development, data-driven roles or further research.

What You'll Learn

Foundations of artificial intelligence and machine learning

Computational intelligence and nature-inspired algorithms

Artificial neural networks and applications of deep learning

Evolutionary computation and adaptive behaviour in natural systems

Data science, including collecting, cleaning and analysing data

Programming and problem solving using modern languages such as Python

Human-centred software engineering and web technologies

Statistics and probability for data science

Legal, ethical and societal issues surrounding AI and data

Research skills and an independent AI research and development project

Learning Outcomes

By the end of the course, students will understand computer science and artificial intelligence from their mathematical and scientific foundations through to their practical use, including the legal frameworks and standards that govern them. They will be able to model, design, build, test and evaluate complex computing systems that meet defined requirements within real-world constraints of time and budget. Students will learn to apply AI techniques such as machine learning and deep learning to real problems, to judge critically which tools and methods suit a given situation, and to recognise the risks and safety concerns involved in deploying intelligent systems. Practical work in computer laboratories builds fluency in programming and data analysis, while group projects develop teamwork, communication and project planning. Awareness of data ethics, security, inclusion and sustainability supports responsible professional practice. The final-year research project and optional modules allow students to specialise in the areas of AI that interest them most, preparing them for careers in technology, finance, healthcare, public policy or postgraduate study.