Modules include work based on research by the Computer Science and Artificial Intelligence Paradigms (CSAIP) research group.

• Project Management and Research Methodology – 20 credits
  Project Management and Research Methodology provides students with the opportunity to plan a project using appropriate methods, techniques and tools, taking into account relevant risks and ethical issues, and undertake a literature review and other development activities to improve their understanding of the situation and/or produce organisational change.
  
  
• Principles of Computing – 20 credits
  Principles of Computing provides students with the opportunity to demonstrate a comprehensive understanding of current developments in computer technology, programming and database systems and to apply appropriate practices, tools and techniques to produce a solution to a problem where there are many interacting factors.
  
  
• Computational Applications Of Artificial Intelligence -20 Credits
  Computational application of artificial intelligence provides students with the opportunity to gain practical knowledge of computational applications used in the field of artificial intelligence and managing complex data sets such that they can assess the practical situations and interpret real-world applications using the concepts of statistical analysis and its value in Data science.
  
  
• Knowledge-Based Systems – 20 credits
  Knowledge-Based Systems provides students with the opportunity to gain a broad introduction to applicable artificial intelligence alongside practical skills designing and developing knowledge-based systems used to support human decision-making, learning and action, and appreciate their implications to society.
  
  
• Machine Learning and Autonomous Systems – 20 credits
  Machine Learning and Autonomous Systems provides students with the opportunity to build a foundational understanding of machine learning and autonomous systems, approaches to their design and development, areas of application, available tools and their implications to society.
  
  
• Deep Learning – 20 credits
  Deep Learning provides students with the opportunity to build on their knowledge of machine learning and explore the field of deep learning, areas of their application, approaches to the design and development of solutions to problems and available tools.
  
  
• MSc Project – 60 credits

This AI masters is aimed at graduates with engineering, science, IT, mathematics or business backgrounds who have strong numeracy and IT skills.

It is delivered in four major blocks to offer an intensive but focused learning pattern. Full-time students will typically spend 12 hours in classes and 24 hours outside of classes each week.

If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects.

You will need to spend a significant amount of time working independently, reading and preparing for assessments. 

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.

Assessment is primarily by coursework (94%), varying from a research-style paper or essay to practical assignments.

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.