Keele University

What you'll study

The programme covers a balance of foundational computer science and focused artificial intelligence subjects. Core topics include programming, data structures and algorithms, software engineering, databases and computer systems, taught alongside AI-specific modules such as machine learning, knowledge representation, reasoning, natural language processing and intelligent agents.

Teaching emphasises practical development and project work: students gain experience with contemporary programming languages, machine learning libraries, data handling and software development practices. Laboratory sessions and coursework develop skills in building, testing and evaluating intelligent systems.

Typical year-by-year structure:

• Year 1: Introduction to programming, mathematics for computing, foundations of computer systems and introductory AI concepts.
• Year 2: Core computer science modules (algorithms, databases, software engineering) plus intermediate AI modules (machine learning, search and optimisation, probabilistic methods).
• Year 3: Advanced AI topics (natural language processing, deep learning, multi-agent systems), elective modules to broaden or specialise, and an independent final-year project applying AI techniques to a substantive problem.

There is usually the option to take a sandwich/placement year between years 2 and 3 or to study abroad, providing industry experience or international exposure. Assessment is by a mix of exams, coursework, laboratory practicals and project deliverables.

Entry requirements

Applicants are expected to have a strong quantitative background. Typical offers request A-levels (or equivalent) including mathematics or a numerate subject. Applicants with a level 3 qualification in computing, relevant BTEC (or equivalent vocational qualifications), Scottish Highers/Advanced Highers, or an International Baccalaureate Diploma with suitable higher-level subjects are also considered.

Other considerations include personal statements and references that demonstrate programming experience or an aptitude for analytical problem solving. Mature applicants with relevant work experience and applicants returning to study are welcomed; they may be asked to provide evidence of recent study or professional practice. A good pass in GCSE (or equivalent) English and Mathematics is normally expected.

Career prospects

Graduates from this degree are equipped for a wide range of roles in software and data-driven industries. Common career paths include software developer/engineer, machine learning engineer, data scientist/analyst, AI developer, systems analyst, and roles in robotics or automation. The programme also prepares students for postgraduate research (MSc/PhD) in computer science and artificial intelligence.

Placement year options and industry-facing projects help build employability through real-world experience, professional contacts and an applied final project that can be presented to employers.

Why study at Keele University

Keele offers a campus-based university experience with a supportive learning environment and relatively small cohort sizes that encourage staff-student interaction. The School of Computing and Mathematics provides dedicated computing labs, access to modern development and AI tools, and teaching delivered by staff active in research and industry collaboration.

The university’s interdisciplinary approach allows students to take complementary modules from other subjects, and there are opportunities for placements and industry projects. Keele also places emphasis on student support services, employability activities and personal tutoring to help students transition into higher education and into their chosen careers.