admin Programme Overview
This programme provides advanced study of artificial intelligence methods, applications and the questions raised by their use in organisations and society. The curriculum examines machine learning, deep learning, language technologies, data, optimisation and AI governance, linking conceptual study with current questions in responsible design and evaluation of intelligent systems.
You will critically investigate AI techniques and application cases, considering model performance alongside the quality, limits and consequences of automated decisions. You will work through guided activities, applied scenarios and peer discussion, developing a disciplined approach to evidence, communication and independent work.
Responsible AI is treated as a core capability, with sustained attention to fairness, accountability, explainability and meaningful human oversight. Learning is organised for online participation, with clear milestones, tutor feedback and space to connect ideas across the programme. Throughout, opportunities to compare perspectives and receive formative feedback help consolidate your understanding, refine your judgement and prepare you to engage confidently with unfamiliar professional challenges. The final stage invites you to bring your learning together in a sustained piece of work.
What You’ll Learn
- Critically evaluate advanced AI methods and applications
- Develop and assess machine learning models
- Apply deep learning and language processing concepts
- Analyse data, performance and model limitations
- Address governance and ethical challenges in AI
- Complete an independent AI research or application project
Programme Structure
Core Modules
- Advanced Machine Learning
- Deep Learning Concepts and Practice
- Natural Language Processing
- AI Systems Engineering
- Responsible AI and Governance
Research and Applied Practice
- Research Methods for Artificial Intelligence
Final Project
- MSc Artificial Intelligence Dissertation or Applied Capstone
Entry Requirements
Applicants are normally expected to hold a relevant undergraduate degree or demonstrate equivalent professional experience. Applications from adjacent disciplines may be considered where applicants can show appropriate technical knowledge and readiness for advanced study.
Applicants should be able to demonstrate English-language proficiency appropriate for degree-level study. Equivalent evidence of English proficiency may be considered as part of the application.
Assessment
Assessment may include technical investigations, applied coursework, reports, prototypes, critical analyses, presentations, portfolio evidence and a substantial capstone project or dissertation. Examination-style assessments may be used where appropriate to assess core concepts.
Career Opportunities
- Machine Learning Engineer
- AI Solutions Consultant
- Data Scientist
- AI Product Manager
- Applied AI Researcher
- Responsible AI Analyst
Further Study
Graduates may progress to doctoral study where appropriate or pursue advanced professional development in machine learning, AI engineering, data science or AI governance.