MEng Computer Science with Cyber Security
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
The MEng (Hons) Computer Science with Cyber Security is a computer science and software engineering degree centred on the protection of digital systems and networks. Core topics include Programming, Systems Design, Computer Architecture, Embedded Systems, Data Analysis, Research Methods, and Artificial Intelligence & Machine Learning. Students complete a focused cyber security project and can undertake a placement year to gain professional workplace experience before graduation. Throughout the four-year course, students progress from fundamental concepts to advanced specialisms. The first year establishes core foundations through modules such as Software 1: Foundations of Programming for Computer Science, Theory 1: Mathematical Foundations of Computer Science, and Systems and Devices 1: Introduction to Computer Architectures. The second year builds technical knowledge with modules including Engineering 1: Systems and Software Engineering, Systems and Devices 2: Operating Systems, Security and Networking, and Intelligent Systems: Machine Learning and Optimisation. The third and fourth years advance into specialized study through compulsory modules like Cryptography Theory and Practice, Ethical Hacking, Analysis and Investigation, and Network Security, alongside a group project for integrated masters students. Optional study areas include subjects such as Autonomous Robots, Deep Learning, and Embedded Systems Design and Implementation.
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: Systems and Software 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 (Cyber Security topic)
- Cryptography Theory and Practice
- Ethical Hacking, Analysis and Investigation
- Network Security
- Quantum Computation
- Human Factors: Technology in Context
- AI Search and Logic
- Autonomous Robots
- Embedded Systems Design and Implementation
- Engineering 2: Automated Software Engineering
- High-Integrity Systems Engineering
- High-Performance Parallel and Distributed Systems
- Deep Learning
- Legal Practice, Technology and Computer Science
- Player Experiences in Digital Games
- Qualitative Approaches to Investigating UX
- Research Methods in Computer Science
- Cloud based Data Analysis
- Game Design & Development in Real-Time Engines
- Governance of Data Science
- Engineering LLM-Based Agents and Applications
- Large Language Models
- Natural Language Processing
- Group Project (Integrated Masters)
- Cryptography Theory and Practice
- Ethical Hacking, Analysis and Investigation
- Network Security
- AI Problem Solving with Search and Logic
- Autonomous Robotic Systems Engineering
- Computer Vision and Graphics
- Embedded Systems Design and Implementation
- Engineering 2: Automated Software Engineering
- Evolutionary and Adaptive Computing
- High-Integrity Systems Engineering
- High-Performance Parallel and Distributed Systems
- Human Factors: Technology in Context
- Intelligent Systems: Probabilistic and Deep Learning
- Player Experiences in Digital Games
- Qualitative Approaches to Investigating UX
- Quantum Computation
- Research Methods in Computer Science