MSc AI and Machine Learning

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.

Topic include: Fundamentals of Machine Learning, Data Preprocessing and Cleaning, Supervised Learning Algorithms, Unsupervised Learning and Dimensionality Reduction, Feature Engineering and Selection, Model Evaluation and Validation, Hyperparameter Tuning and Optimization, Ensemble Methods and Foundations for Deep Learning.

Full module specification Led by Dr Sadaqat ur Rehman

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.

Topic include: Agentic AI Overview, LLM Integration Techniques, Managing Conversation Context, Advanced Prompt Engineering, Developing LLM Agents, Safety and Human Oversight, Semantic Retrieval and Embeddings, Secure Data Integration and Fine-Tuning and Deployment.

Full module specification Led by Dr Vimal Dwivedi

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.

Topic include: Business AI Fundamentals, AI Limitations and Boundaries, AI in Strategic Decision-Making, AI Deployment Challenges, AI and Human Collaboration, Organisational Transformation, Risk Management in AI, Ethical AI and Social Responsibility and Future AI Trends.

Full module specification Led by Dr Yuri Jiang

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.

Topic include: Principles of Innovation, Leadership Styles, Fostering Creativity, Managing Innovation Teams, Navigating Change, Risk Management, Scaling Innovation, Collaboration Models and Digital Transformation.

Full module specification Led by Dr Milyan Hills

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.

Topic include: Human-Centred Design, Understanding Users, UX Design Techniques, Usability Evaluation, Information Architecture, Design Thinking, Advanced Design Principles, Error Prevention & Recovery and Agile Collaboration.

Full module specification Led by Dr Ramy Hammady

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.

Topic include: Computer Vision Fundamentals, Feature Detection and Description, Image Segmentation Techniques, Advanced Object Detection, Deep Learning Foundations, Vision Transformer Architectures, Implementing Deep Learning Frameworks, Transfer Learning and Network Adaptation and Real-Time Processing and Multi-Object Tracking.

Full module specification Led by Dr Vimal Dwivedi

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.

Topic include: Neural Network Fundamentals, Training Deep Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention Mechanisms & Transformers, Autoencoders & Representation Learning, Generative Models & GANs, Optimisation Techniques in Deep Learning and Hyperparameter Tuning & Model Evaluation.

Full module specification

Led by Dr Adnan Qureshi

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.

Full module specification Led by Dr Milyan Hills