MSc in
Artificial Intelligence

Evaluate where AI can create business value, where it falls short and what successful adoption requires. Explore implementation challenges, human–AI collaboration, risk and ethics so you can make better decisions about how your organisation uses AI.

Learn to build and evaluate machine learning models using Python. Prepare data, compare algorithms and test how well models perform on prediction and classification tasks. This technical option develops practical skills in data preparation, model selection and validation.

Build AI agents that connect language models, tools and data to carry out multi-step tasks. Explore how to manage conversation context, integrate information securely and include human oversight. This technical option involves practical programming and AI system development.

Master the skills to design and implement complex vision systems that solve real-world challenges across diverse industries. By engaging with advanced techniques and tools, you will be prepared to make a tangible impact in fields like healthcare, automotive, and retail. This module offers a deep dive into cutting-edge methods, equipping you with the knowledge to innovate and excel in the evolving landscape of computer vision.

Delve into the world where technology meets intelligence. This module provides not just an understanding but a mastery over innovative neural network architectures. It's designed to elevate your grasp on complex data handling, paving the way for creating solutions to intricate problems using cutting-edge deep learning techniques.

Understand how digital businesses create value and how technology decisions are shaped by markets, organisational culture and commercial priorities. Use that understanding to assess opportunities, navigate internal politics and plan your own career development.

Learn to turn digital priorities into organised delivery. Apply agile, Scrum and lean approaches while managing stakeholders, budgets, resources and risk. Understand how governance and change management help keep projects aligned with business goals.

Develop your approach to leading innovation when priorities compete and outcomes are uncertain. Explore how to support creative teams, manage resistance, assess risk and scale promising ideas while keeping work connected to organisational goals.

Learn how to design digital systems around the people who use them. Investigate user needs and workflows, evaluate usability and identify barriers to adoption. Develop the understanding to make better design decisions and work more effectively with design and delivery teams.

Gain the essential skills to launch, manage, scale, and exit successful online businesses in the age of AI. Learn how to assess a digital business opportunity and develop a credible route to market. Explore business models, product–market fit, finance, marketing and operations, including the decisions involved in launching, growing and exiting a venture.

Develop practical programming skills in R and Python to prepare, analyse and visualise data. Work with data structures, libraries and common analysis techniques so you can turn raw datasets into evidence for decisions.

Learn to turn business needs into clear, prioritised requirements that delivery teams can act on. Practise identifying stakeholder needs, defining system behaviour, controlling scope and checking that the proposed solution addresses the original problem.

Bring your learning together in an independent project, supported by one-to-one supervision and structured seminars. Investigate a problem, develop and evaluate a practical response, and communicate your findings. Depending on your approved proposal, your output could include a framework, implementation plan, analytical tool or prototype.