MSci Computer Science and Mathematics
Entry requirements
A level: A*AA including Maths IB: 38 (7,6,6 HL) including HL Maths BTEC: BTEC Level 3 National Extended Certificate: D* plus two A levels at Grades A*A including Maths BTEC Level 3 National Extended Diploma and National Diploma not accepted for MSci but considered for BSc in combination with A level Maths Preferred BTEC: Computing, IT
About this course
MSci (Hons) in Computer Science and Mathematics, a mathematics and computer science degree bridging computational and analytical techniques. Core topics include Programming, Statistics, Mathematical Modelling, Research Methods, Ethics & Professional Practice, Entrepreneurship, Artificial Intelligence & Machine Learning. Students complete a dedicated project combining both disciplines in the third year, alongside opportunities for specialized study and an extended master's curriculum. The first year covers foundational principles through Introduction to Programming and Databases, Analysis I, Calculus I, and Logic for Computer Science. The second year progresses with Artificial Intelligence and Machine Learning, Professional Training Preparation, Object-oriented Programming Team Project, and Formal Languages, Theory of Computation, and Applications, alongside optional choices such as Computer Graphics and Mechanics. The third year incorporates the Computer Science and Mathematics Project alongside numerous optional modules spanning subjects like Software Engineering: Practices and Principles, Algorithm Analysis, and Cyber Risk Management. The final fourth year centers on advanced study through Managing a Project Team, Thesis Project, Learning Evaluation in a Specialised Subject, Innovation and Technology, Mathematical Modelling I, and Mathematical Modelling II.
Modules
- Introduction to Programming and Databases
- Analysis I
- Calculus I
- Logic for Computer Science
- Fundamentals of Software Engineering
- Linear Algebra and Geometry I
- Introduction to Algorithms
- Foundations of Artificial Intelligence
- Numerical Methods
- Artificial Intelligence and Machine Learning
- Professional Training Preparation
- Object-oriented Programming Team Project
- Formal Languages, Theory of Computation, and Applications
- Introductory Probability and Statistics
- Calculus II
- Linear Algebra and Geometry II
- ODEs and Calculus of Variations
- Computer Graphics
- Mechanics
- Computational Methods for Differential Equations
- Elements of Topology
- Computer Science and Mathematics Project
- Linear Differential Equations
- Algebra
- Software Engineering: Practices and Principles
- Enterprise Resource Planning Systems
- Agent-Based Systems
- Algorithm Analysis
- Distributed Systems
- Computer Animation
- Probability Theory
- Applied Statistics
- Introduction to Differential Geometry
- Advanced Numerical Methods
- Dynamical Systems
- Asymptotic Methods
- Operational Research
- Cyber Risk Management
- Human Factors and Cyber Security
- Analysis II
- Mobile Application Development
- Web Systems: Security, Architecture, Development
- Robotics
- Advanced Artificial Intelligence Systems
- Data Mining and Machine Learning
- Cryptography and Network Security
- Computer Vision
- Complex Analysis
- Statistical Modelling
- Medical Statistics
- Studies in Science and Mathematics Education
- Vibrations and Waves
- Game Theory
- Computational Methods in Finance
- Mathematical Biology
- Digital Forensics
- Applied Cryptography
- Managing a Project Team
- Thesis Project
- Learning Evaluation in a Specialised Subject
- Innovation and Technology
- Mathematical Modelling I
- Mathematical Modelling II