Upcoming Courses

MSc Applied Artificial Intelligence

Develop a deep understanding of AI systems, including generative AI, machine learning, and computer vision
Understand how to deploy AI solutions based on the analysis of client needs
Identify ethical and societal impacts of applying AI
Collaborate with our industry contacts on live projects

You’ll develop the multidisciplinary skills needed to understand what AI solutions are available and how they can be successfully deployed in a wide range of contexts from any discipline. The course focuses on the use of existing AI tools and technologies across AI systems, such as ChatGPT, Gemini, Copilot, Azure, and Google Colab.

You’ll explore and learn the fundamental principles that underpin AI systems. This includes machine learning, deep learning, data mining, natural language processing, computer vision, and intelligent systems. Through a “no-code” web approach, you’ll explore AI model creators and develop an awareness of available AI systems. This will also develop an appreciation for how data interacts with AI.

Using that knowledge, you’ll be working with clients on projects to understand their business needs and how AI technologies and tools can be positively exploited. During those projects, you’ll have regular scrum meetings with academics and clients that identify narratives, learning needs and action plans to progress. Through that collaboration and critical evaluation, you’ll deploy an optimal AI solution to meet the real-world needs of the client. For example, you could be deploying Chatbots as first-line triage to support wellbeing, identifying dangerous warehouse environments to improve site health and safety, or trend analysis of transport and footfall data.

Alongside developing your understanding of how to apply AI, you will also consider the challenges, requirements and limitations of AI tools.

Due to launch April / May 2026

MSc Computing with Artificial Intelligence

Learn how to program for Artificial Intelligence
Understand ethical and data biases in AI solutions
Gain knowledge across related topics, such as database management and web
Collaborate with our industry contacts on live projects

Designed for graduates without a computing background, the course is designed to build up your fundamental computing skills required to achieve in the advanced topic of Artificial Intelligence (AI) technologies. Through project-based learning, you will develop professional skills while tackling real-world client projects.

You’ll develop fundamental programming skills in Python and C#, alongside database development and web technologies. This will serve as your essential foundation for understanding and applying artificial intelligence technologies.

Building upon those foundational skills, you will develop an appreciation of professional software development lifecycles, project management, and research skills alongside your specialisation into AI technologies. You will learn how to develop and deploy techniques and technologies including:

Building AI models using supervised, unsupervised, reinforcement learning
Natural language processing (NLP) and generative AI
Explainable & trustworthy AI
Computer vision
Scale and use agentic AI using microservices architectures
Azure AI solutions
K-means clustering
Convolution neural network (CNN) models

Using platforms including Visual Studio Code and Jupyter Notebook, you will use PyTorch, Keras and TensorFlow libraries as you develop your understanding of AI technologies and solutions.

Your skills are developed through real-world projects that are set by our industry collaborators. During these projects, you will have regular meetings with the clients to identify needs and manage progress. Examples of projects include AI-based recommendation systems for optimal space utilisation, and efficient logistic / transportation route planning and management.

You will showcase your skills and knowledge developed throughout the course by undertaking a research-led AI project. This is your opportunity to further specialise in a particular area of AI, with regular support from your academic supervisor.

Due to launch April / May 2026