Loughborough University

What you'll study

This master's combines core AI theory with hands-on practice and a substantial research or industry-facing project. Teaching typically includes a mix of compulsory and optional modules, followed by an individual dissertation or group project that applies methods to a real problem.

• Core topics: supervised and unsupervised machine learning, probabilistic modelling and Bayesian methods, optimisation techniques, and research methods for computing.
• Advanced AI areas: deep learning and neural networks, computer vision, natural language processing, reinforcement learning and decision-making under uncertainty.
• Systems and engineering: data engineering and scalability, deployment of AI systems, software engineering for intelligent systems and considerations for real-time and embedded AI where relevant.
• Ethics and governance: responsible AI, fairness, interpretability and the social impact of AI systems are integrated across teaching and assessment.
• Project: an individual dissertation or team project supervised by academic staff, often drawing on Loughborough’s research groups and industrial partners to work on applied problems or methodological research.

Entry requirements

Applicants are normally expected to hold a good honours degree (equivalent to a UK 2:1) in a relevant subject such as computer science, mathematics, statistics, electrical/electronic engineering or a closely related discipline. Candidates with a strong numerate background from other disciplines, or with substantial relevant professional experience, may also be considered. For those whose first language is not English, a recognised English language qualification is required; typical guidance is an overall IELTS score around the mid-6s with minimum component scores, or an equivalent qualification.

Career prospects

Graduates move into a wide range of technical and research-focused roles. Common career paths include:

• Machine learning engineer or applied AI engineer, building and deploying predictive models and intelligent systems.
• Data scientist or data analyst roles across finance, healthcare, retail, manufacturing and public sector organisations.
• Specialist roles in computer vision, natural language processing, robotics and autonomous systems.
• Consultancy, product management and technical leadership positions that require an understanding of AI capabilities and limitations.
• Further academic research and PhD study in machine learning, AI or related fields.

Why study at Loughborough University

Loughborough offers research-led teaching within a strong computing and engineering environment, with access to well-equipped laboratories and high-performance computing resources. The university has active research groups working on machine learning, data science and autonomous systems, and staff engage with industry through collaborative projects and knowledge transfer, providing opportunities for applied projects and placements. The campus-focused student experience, careers support and strong employer links help graduates transition into professional roles or further study.