Computer Science and Mathematics

Are you drawn to the practical power and potential of computing and the beauty and logic of the mathematics behind it?

Computing has always relied on mathematical models and algorithms but mathematics also relies heavily on computers for exploring concepts, modelling ideas, problem-solving and even generating proofs. Both mathematics and computer science inform almost every aspect of our modern lives and this three-year joint honours programme allows you to immerse yourself in both and combine abstract concepts and fascinating theories with hands-on practical experience.

Our progressive curriculum is delivered by inspiring mathematicians and computer scientists and informed by input from industry. You will gain a solid grounding in all the fundamentals of pure and applied mathematics, whilst learning about computer programming, software engineering, algorithms and complexity. In computer science our focus is on contemporary technologies such as Web 2.0 and distributed and embedded systems. You will have the chance to experiment in well-equipped laboratories with cutting-edge technologies that are transforming the way we live and work. You will also gain transferrable skills such as project management, time management, team working, data handling, research and presentation. The programme's modular structure means you can tailor your studies to your own interests, whilst maintaining an equal split between the two disciplines.

Our Mathematics and Computer Science departments are highly respected for the quality of their research and teaching. They offer friendly and supportive learning environments with excellent facilities. We are one of only seven computer science departments in the UK to hold the Athena SWAN bronze award for increasing female participation in computer science. We offer short-term summer work placements and a dedicated personal adviser to guide you through your studies. You will also be welcome to join our thriving Computing Society.

Course Modules

Core Modules

Year 1

• Object Oriented Programming I

• Object Oriented Programming II

• Programming laboratory

• Software Design

• Calculus I

• Calculus II

• Introduction to Pure Mathematics

• Linear Algebra I

• Academic Integrity

Year 2

• Software Engineering

• Algorithms and Complexity

• Team Project

• Linear Algebra II

• Probability Theory

Year 3

• All modules are optional

Optional Modules

Below is a taster of some of the exciting optional modules that students on the course could choose from during this academic year. Please be aware these do change over time, and optional modules may be withdrawn or new ones added.

Year 1

• All modules are core

Year 2

• Symbolic Artificial Intelligence

• Ring Theory

• Complex Analysis

• Ordinary Differential Equations and Fourier Analysis

• Vector Calculus

• Introduction to Information Security

• Databases

Year 3

• Half Unit Project

• Full Unit Project

• Intelligent Agents and Multi-agent Systems

• Machine Learning

• IT Project Management

• Compilers and Code Generation

• Functional Programming and Applications

• Number Theory

• Quantum Theory 1

• Inference

• Combinatorics

• Markov Chains and Applications

• Quantum Information and Coding

• Financial Mathematics I

• Financial Mathematics II

• Cryptography

• Topology

• Group Theory

• Introduction to Optimisation

• Game Theory

• Deep Learning

• Security Management

• Software Verification

• Advanced Algorithms & Complexity

• Quantum Computing

• Natural Language Processing

• Applications of Vector Calculus

• Graph Theory

https://www.royalholloway.ac.uk/studying-here/undergraduate/computer-science/computer-science-and-mathematics/

The course has a flexible, modular structure. In addition to our compulsory courses in each discipline you will be free to choose between a range of optional modules.

We use a variety of teaching methods and there is a strong focus on small group teaching. You will mostly learn through lectures, small group tutorials, practical sessions and problem-solving classes, supervised computing laboratory work, group work and coursework. Our programming and software engineering teaching is very hands on, allowing you to learn at your own pace, whatever your previous level of experience. You will also be expected to complete private study and revision, worksheets, team work and independent project work outside of class time, with access to a wide range of resources including Moodle, the University’s comprehensive e-learning facility.

For lecture-based courses, assessment is usually by a written examination at the end of the year in which the course is taken. Most of our courses also involve an element of coursework, which might be examined through project reports, essays, oral presentations or software submissions.