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Home The Role of Technology in Education and Training in the UK
Next Date: September 2026
Artificial Intelligence (AI) impacts many aspects of our lives, from life-style choices to healthcare, advanced engineering and self-driving vehicles. The study of the foundations of AI is multi-disciplinary, incorporating aspects of computer science, mathematics/statistics, psychology and in terms of its impact and application, natural, physical and social sciences.
This course is designed for students with a numerate background (for example, an undergraduate degree in mathematics, economics, engineering, physics or chemistry) as well as graduates already working in industry.
During the course, you'll explore a range of topics, covering both theoretical and practical aspects of AI.
The programme consists of lectures, practical work and an individual dissertation project, in which you undertake a significant AI-themed research project under the supervision of a member of staff.
An essential part of AI is 'learning from data' and the programme will include training on software development for the analysis of data, or on robust data analysis methodologies to cope with missing or corrupted data. At the end of the course, graduates will be prepared for work in a wide variety of jobs in which comprehensive knowledge and understanding of AI is required.
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£
Minimum 2:1 undergraduate honours degree in a relevant subject.
Subject requirements
We accept degrees in the following subject areas:
- Artificial Intelligence
- Chemistry
- Computer Science
- Economics
- Mathematics
- Physics
- Any Engineering subject
We may be able to consider degrees in Computer or Computing.
Apply for partial scholarships
Core modules:
- Scalable Machine Learning
- Text Processing
- Machine Learning and Adaptive Intelligence
- Natural Language Processing
- Professional Issues
- Team Project
- Data Science with Python
- Artificial Intelligence Dissertation Project
Optional modules:
- Modelling and Simulation of Natural Systems
- Network Performance Analysis
- Parallel Computing with Graphical Processing Units (GPUs)
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