MEng Computer Science with Artificial Intelligence
Entry requirements
A level: A*AA including Mathematics. If you are studying towards a fourth A level, we will make an alternative offer of AAAA including Mathematics. IB: 37 points overall, including 5 in Higher Level Mathematics (either Analysis and Approaches or Applications and Interpretations), or 6 in Standard Level Mathematics (Analysis and Approaches). BTEC: DDD plus grade B in A level Mathematics (or equivalent qualification) We consider a range of BTEC qualifications equivalent to 3 A Levels, or in combination with A Levels or other qualifications. For example: Distinction, Distinction in BTEC Level 3 National Diploma plus A in A Level Mathematics Distinction in BTEC Level 3 National Extended Certificate plus AA at A level including Mathematics Distinction, Distinction in 2 BTEC Level 3 National Extended Certificates plus A in A Level Mathematics
About this course
MEng (Hons) Computer Science with Artificial Intelligence, a computer science and computer science (artificial intelligence) degree centered on software development and intelligent system engineering. Core topics include Programming, Systems Design, Computer Architecture, Embedded Systems, Data Analysis, Research Methods, and Artificial Intelligence & Machine Learning. The curriculum includes an integrated masters group project and offers an optional placement year in industry. The first year covers core programming and mathematical foundations through modules such as Software 1: Foundations of Programming for Computer Science, Theory 1: Mathematical Foundations of Computer Science, Human-Computer Interaction, and Software 2: Object-Oriented Data Structures and Algorithms. The second year progresses into systems and engineering via Engineering 1: Software and Systems Engineering, Systems and Devices 2: Operating Systems, Security and Networking, Theory 3: Computability, Complexity and Logic, and Intelligent Systems: Machine Learning and Optimisation. Year three focuses on specialised artificial intelligence topics through compulsory study in Computer Science Project (Artificial Intelligence topic), AI Search and Logic, Autonomous Robots, Deep Learning, Engineering LLM-Based Agents and Applications, Large Language Models, and Natural Language Processing. Optional modules across later stages span areas such as Cryptography Theory and Practice, Embedded Systems Design and Implementation, Engineering 2: Automated Software Engineering, and Ethical Hacking, Analysis and Investigation. The final fourth year centers on advanced study and the Group Project (Integrated Masters).
Modules
- Software 1: Foundations of Programming for Computer Science
- Theory 1: Mathematical Foundations of Computer Science
- Human-Computer Interaction
- Software 2: Object-Oriented Data Structures and Algorithms
- Systems and Devices 1: Introduction to Computer Architectures
- Theory 2: Formal Languages and Automata
- Engineering 1: Software and Systems Engineering
- Systems and Devices 2: Operating Systems, Security and Networking
- Theory 3: Computability, Complexity and Logic
- Intelligent Systems: Machine Learning and Optimisation
- Data: Introduction to Data Science
- Systems and Devices 3: Advanced Computer Systems
- Computer Science Project (Artificial Intelligence topic)
- AI Search and Logic
- Autonomous Robots
- Deep Learning
- Engineering LLM-Based Agents and Applications
- Large Language Models
- Natural Language Processing
- Cryptography Theory and Practice
- Embedded Systems Design and Implementation
- Engineering 2: Automated Software Engineering
- Ethical Hacking, Analysis and Investigation
- High-Integrity Systems Engineering
- High-Performance Parallel and Distributed Systems
- Human Factors: Technology in Context
- Legal Practice, Technology and Computer Science
- Network Security
- Player Experiences in Digital Games
- Qualitative Approaches to Investigating UX
- Quantum Computation
- Research Methods in Computer Science
- Cloud based Data Analysis
- Game Design & Development in Real-Time Engines
- Governance of Data Science
- Group Project (Integrated Masters)
- Cryptography Theory and Practice
- Embedded Systems Design and Implementation
- Engineering 2: Automated Software Engineering
- Ethical Hacking, Analysis and Investigation
- High-Integrity Systems Engineering
- High-Performance Parallel and Distributed Systems
- Human Factors: Technology in Context
- Network Security
- Player Experiences in Digital Games
- Qualitative Approaches to Investigating UX
- Quantum Computation
- Research Methods in Computer Science