MSci Artificial Intelligence
Entry requirements
A-Level: AAA-AAB IB: 36/666-34/665 BTEC: DDD
About this course
MSci in Artificial Intelligence, a computer science degree centred on artificial intelligence and machine learning principles. Core topics include Programming, Computer Architecture, Data Analysis, Statistics, Mathematical Modelling, Research Methods, Project Management, Clinical Skills, Critical & Analytical Thinking, and Artificial Intelligence & Machine Learning. Students complete an individual research project in the final year alongside group software development work. Following foundational studies in the first year covering Programming, Object-Oriented Programming, and Data Structures and Algorithms, the second year introduces Machine Learning and Data Science, Team Project, and Artificial Intelligence and Applications alongside optional modules such as Computational Intelligence and Programming for Prompt Engineering. Third-year students undertake an Individual Literature Review and Project, complemented by optional choices like Computer Vision and Probabilistic Machine Learning. The final year centres on advanced independent study through the Individual Research Project and Group Development Project, with further optional topics including Deep Learning, Large Language Models and Applications, and AI in Healthcare.
Modules
- Fundamentals of Machine Learning
- Programming
- Social and Professional Issues of the Information Age
- Object-Oriented Programming
- Computers and the Internet
- Data Structures and Algorithms
- Discrete Mathematics for Computer Science
- Computational Mathematics
- Employability and Placement Preparation for Computer Scientists
- Machine Learning and Data Science
- Introduction to Prompt Engineering
- Team Project
- Software Development
- Database Theory and Design
- Artificial Intelligence and Applications
- Computational Intelligence
- Programming for Prompt Engineering
- Employability and Placement Preparation for Computer Scientists
- Data Science in Society
- Individual Literature Review and Project
- Data Science at Scale
- Computer Vision
- Social Networks and Text Analysis
- Probabilistic Machine Learning
- Foundations of Human-Centred AI
- Nature-Inspired Computation
- Computability and Complexity
- Algorithms that Changed the World
- High-Performance Computing
- Group Development Project
- Individual Research Project
- Text Mining and Natural Language Processing
- Deep Learning
- Generative AI Applications
- Large Language Models and Applications
- AI in Healthcare
- AI in Environment
- Machine Learning
- Evolutionary Computation and Optimisation
- Computer Modelling and Simulation