MComp Computer Science (Artificial Intelligence)
Entry requirements
A Level: A*AA; AAA IB: 38, with 6 in Higher Level Maths; 36, with 6 in Higher Level Maths and Computer Science; 36, with 6 in Higher Level Maths, and A in a computer science-based extended essay; 34, with 6 in Higher Level Maths and 5 in Higher Level Computer Science, and A in a computer science-based extended essay
About this course
MComp in Computer Science (Artificial Intelligence), an undergraduate degree centred on computer science and artificial intelligence (artificial intelligence) within the wider field of Electrical and Electronic Engineering and Computer Science and Computer Science (Artificial Intelligence). Core topics include Programming, Systems Design, Computer Architecture, Embedded Systems, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Research Methods, Project Management, Engineering Design, Ethics & Professional Practice, and Artificial Intelligence & Machine Learning. This course represents a one-year extension to the corresponding BSc programme, providing opportunities for advanced specialisation in AI through taught study and a collaborative group research project. The first year covers core principles through Java Programming, Practical Algorithms and Data Structures, Systems and Networks, Introduction to Software Engineering, Foundations of Computer Science, and Introduction to Artificial Intelligence and First Year Reflection. The second year builds competence via Programming Language Principles, Cybersecurity in Action and Professional Issues, Databases and Logic in Computer Science, Automata, Computation and Complexity, Foundations and Applications of Artificial Intelligence, and Software Hut. In the third year, students undertake a Dissertation Project and Deep Learning alongside optional modules spanning areas such as speech and audio processing, 3D computer graphics, internet of things, advanced algorithms, mobile application development, nature-inspired computation, cryptography, and robotics. The final fourth year centres on the Turing Research Project and Self-directed Professional Development, complemented by optional studies in cyber threat hunting, safety-critical systems testing, computer vision, cognitive robotics, parallel computing with GPUs, and reinforcement learning.
Modules
- Introduction to Software Engineering
- Foundations of Computer Science
- Java Programming
- Practical Algorithms and Data Structures
- Systems and Networks
- Introduction to Artificial Intelligence and First Year Reflection
- Programming Language Principles
- Cybersecurity in Action and Professional Issues
- Databases and Logic in Computer Science
- Automata, Computation and Complexity
- Foundations and Applications of Artificial Intelligence
- Software Hut
- Dissertation Project
- Deep Learning
- Introduction to Speech and Audio Processing
- 3D Computer Graphics and Image Processing
- Security and Internet of Things
- Advanced Algorithms and Programming Semantics
- Advanced Software Engineering
- Undergraduate Ambassadors Scheme in Computer Science
- Foundations of Natural Language Processing
- Mobile Application Development
- Nature-inspired Computation and Modelling
- Cryptography
- Robotics
- Turing Research Project
- Self-directed Professional Development
- Cyber Threat Hunting and Digital Forensics
- Testing and verification in safety-critical systems
- Cybersecurity Team Project
- Computer Vision
- Human-Computer Interaction and Visual Analytics
- Cognitive and Biomimetic Robotics
- Parallel Computing with Graphical Processing Units (GPUs)
- Development of Secure Software
- Speech Technology
- Software and Hardware Verification
- Reinforcement Learning