City University

What you'll study

The MSc Artificial Intelligence combines core taught modules with practical laboratory work and an independent research or industry project. Core topics typically cover machine learning foundations, deep learning, probabilistic modelling and inference, and optimisation techniques. Students also study applied areas such as natural language processing, computer vision, reinforcement learning and ethical, legal and social implications of AI.

Teaching emphasises hands-on implementation: you will work with standard AI frameworks, develop end-to-end systems, and complete case studies grounded in real-world datasets. Assessment is through a mixture of coursework, project reports, practical assignments and a substantial individual dissertation or industry-focused project in the final term.

The programme structure normally consists of a set of compulsory modules that build the mathematical and algorithmic core, optional modules that let you specialise, and a major project. Typical module examples include:

• Machine Learning and Statistical Methods
• Deep Learning and Neural Networks
• Probabilistic Models and Bayesian Inference
• Natural Language Processing
• Computer Vision
• Reinforcement Learning and Sequential Decision Making
• AI Ethics, Governance and Responsible Innovation
• Individual Project or Industry Placement Project

Entry requirements

Applicants are expected to hold a good undergraduate degree in Computer Science, Mathematics, Engineering, Physics, or a related quantitative discipline. A UK 2:1 honours degree (or international equivalent) is commonly required for direct entry. Candidates with a lower-class degree but with substantial relevant professional experience or evidence of strong quantitative skills may also be considered.

Applicants should have competence in programming (commonly Python) and a grounding in mathematics, especially linear algebra, probability and calculus. Those without a formal computing background may be asked to demonstrate programming ability or complete preparatory modules.

International applicants whose first language is not English must meet the university's English language requirements. Other standard admission checks include references and a personal statement outlining motivations and relevant experience. The programme does not routinely require test scores such as the GRE.

Career prospects

Graduates move into a variety of roles across industry and research. Typical job titles include AI/ML Engineer, Machine Learning Scientist, Data Scientist, Computer Vision Engineer, Natural Language Processing Engineer, and Research Assistant in academic or commercial labs. Alumni also take roles in product management, AI consultancy, and policy or ethics teams that focus on responsible deployment of AI systems.

Because the course is in London, students benefit from proximity to technology companies, financial institutions and startups, which creates opportunities for internships, collaborative projects and industry networking. For students wishing to continue in academia, the programme provides the research training necessary to pursue a PhD.

Why study at City University

City University offers AI teaching delivered by research-active staff with applied and theoretical expertise, combining rigorous foundations with industry-facing practice. The university's central London location provides easy access to a large and diverse technology ecosystem, enabling guest lectures, company projects and recruitment events.

Students benefit from dedicated computing facilities, access to industry datasets through partnerships, and careers support services that help with CVs, interview preparation and employer introductions. The programme is designed to equip graduates with immediately applicable skills while also preparing those who wish to pursue further research.