University of Warwick

What you'll study

The programme emphasises practical application of AI methods to solve problems in industry and services. You will study a mix of core modules that build foundations in machine learning, probabilistic modelling and optimisation, together with applied modules that cover data engineering, AI system design, and decision-making under uncertainty. Teaching blends lectures, labs and project-based learning, often using case studies drawn from manufacturing, supply chains, healthcare and digital services.

• Core topics: supervised and unsupervised learning, deep learning architectures, probabilistic graphical models, reinforcement learning and optimisation methods.
• Applied topics: data engineering and feature pipelines, deployment of AI systems (including MLOps principles), human–AI interaction, explainable AI and ethics for applied settings.
• Practical components: programming labs in Python, hands-on use of common ML frameworks, team projects with industry briefs, and an individual research or industry-linked dissertation.
• Capstone project: a substantial project that requires design, implementation and evaluation of an AI solution to a realistic problem; projects can be academic or in collaboration with industry partners.

Typical structure

The course usually combines taught modules in the first part of the programme with project work and a dissertation in the latter part. Assessment is through a combination of coursework, practical assignments, group projects and the final project report and presentation.

Entry requirements

Applicants are normally expected to hold a good undergraduate degree in a relevant discipline such as computer science, engineering, mathematics, statistics, or a closely related subject. Candidates with significant relevant professional experience, particularly in software development, data science or engineering roles, may also be considered.

• Academic background: a UK upper second class honours (2:1) or equivalent is commonly required; specific offers reflect the applicant's background and experience.
• Mathematical and programming skills: demonstrable ability in programming (typically Python) and a solid grounding in mathematics, including linear algebra, probability and statistics, are expected.
• English language: applicants whose first language is not English will need to meet the University’s English language requirements.
• Supporting materials: a personal statement outlining motivation and relevant experience, references, and where appropriate a CV and examples of past projects or code may be requested.

Career prospects

Graduates go on to roles that develop, deploy and manage AI-driven products and systems across a range of sectors. Typical job titles include machine learning engineer, data scientist, AI engineer, applied researcher and roles in AI product management or analytics engineering. The WMG orientation of the programme means many alumni work in manufacturing, automotive, supply chain, consulting and technology companies where integration of AI with operations and business processes is key.

Beyond industry roles, the programme also prepares students for research degrees or technical leadership positions that require both algorithmic knowledge and an ability to operationalise AI solutions in organisational settings.

Why study at University of Warwick

WMG at the University of Warwick has a strong reputation for bridging academic research and industry practice. The department’s links with technology-intensive companies, manufacturing partners and professional services firms provide rich opportunities for industry-informed teaching, collaborative projects and guest speakers. Students benefit from access to cross-disciplinary expertise across Warwick’s engineering, computer science and business communities.

Warwick’s campus environment combines modern facilities and a supportive student community with proximity to major industrial centres in the Midlands. The programme’s emphasis on applied work, project experience and employability prepares graduates to make an immediate impact in organisations deploying AI technologies.