BSc Computer Science and Mathematics

3 Years On Campus Bachelors Program

University of Manchester

Program Overview

This three‑year joint honours degree brings together the logic and creativity of computer science with the rigour and analytical power of mathematics, giving students an exceptional grounding for careers in technology, data science, software engineering, finance and research. It is perfect for learners who enjoy both abstract reasoning and practical computation, and who want to develop skills that are highly valued across industries.

Curriculum Structure:

Year 1:
In the first year, students dive into core topics in both disciplines, studying units such as First Year Team Project, Introduction to Programming 1 and Introduction to Programming 2 alongside mathematics essentials like Linear Algebra, Mathematical Foundations & Analysis and Probability I. These courses build a balanced foundation in programming, logic, mathematical reasoning and problem‑solving, while optional units like Data Science and Operating Systems allow early exploration of computing themes.

Year 2:
The second year deepens both mathematical and computing expertise with units such as Groups and Geometry and a wide range of optional computer science modules including Algorithms and Data Structures, Introduction to AI and Software Engineering. Alongside this, students can choose advanced mathematics options like Principles of Mathematical Modelling, Partial Differential Equations & Vector Calculus or Probability and Statistics 2 to strengthen analytical depth and modelling capability.

Year 3:
In the final year, learners enjoy broad choice to specialise in areas that reflect their interests, with computer science options including AI and Games, Natural Language Processing and Algorithms and Complexity, as well as mathematical options such as Topology and Analysis, Mathematical Systems and Computation and Multivariate Statistics and Machine Learning. Many students also undertake a Third Year Project Laboratory that allows them to apply their combined skills to a substantial independent or team‑based project.

Focus Areas:
Programming and software development, algorithms and data structures, abstract and applied mathematics, probability and statistics, logical reasoning, computational modelling and independent project work.

Learning Outcomes:
Graduates gain strong computational literacy, deep mathematical reasoning, and the ability to apply analytical and algorithmic thinking to solve complex problems. They emerge with transferable skills in logic, modelling, data interpretation and software design that equip them for a wide range of technical and quantitative roles.

Professional Alignment (Accreditation):
The programme integrates the strengths of Manchester’s Department of Computer Science and School of Mathematics, aligning with professional expectations in both fields and preparing students for careers where high‑level quantitative and computational skills are in demand.

Reputation (Employability Rankings):
The University of Manchester’s computer science offerings are ranked among the UK’s top 10, and the institution is one of the most targeted by employers — meaning graduates are highly sought after by major companies in technology, finance and consulting.

Experiential Learning (Research, Projects, Internships etc.)

The BSc Computer Science and Mathematics programme at The University of Manchester offers students a powerful combination of computational expertise and mathematical reasoning. From the first year, students take part in hands‑on lab sessions and practical workshops where they apply programming concepts, algorithm design, and mathematical logic to real tasks. In computer science units, students work in dedicated computing laboratories with modern development environments and tools, developing software, debugging complex systems, and collaborating on group projects that mirror industry practice. Mathematics components emphasise problem solving, modelling, and analytical thinking backed by specialist mathematical software. Throughout the degree, students engage in collaborative projects, coursework that simulates real challenges, and optional units that allow deeper exploration of topics like artificial intelligence, computational mathematics, or data science. Careers and employability support helps students secure internships and build professional skills in preparation for future careers in technology, analytics, and research.

Experiential learning includes:

Hands‑on programming labs: Work in university computing facilities using current languages and development environments to build real software projects.
Group project work: Collaborate with peers on substantial project units that simulate industry team settings, developing both technical and communication skills.
Mathematical modelling sessions: Apply mathematical theory to computational problems using specialist software and computing resources.
Access to advanced tools: Use up‑to‑date software for programming, algorithm design, simulation, and data analysis throughout the curriculum.
Professional development and internship preparation: Attend workshops on CV building, interview techniques, and internship search strategies to strengthen career readiness.

Academic Environment & Facilities
Students on the BSc Computer Science and Mathematics degree study in a dynamic environment that supports both computation and mathematics. Key facilities include:

Dedicated computing laboratories with up‑to‑date hardware and software tools used in industry, designed to support practical programming and system development.
Collaborative workspaces and study areas where students can work individually or with peers on coding projects, problem sets, and research tasks.
Specialist mathematical computing resources that support modelling, algorithm analysis, and quantitative tasks across the mathematics component of the degree.
Extensive library services through the University of Manchester Library system, providing access to textbooks, technical manuals, journals, and digital research resources across computer science and mathematics.
Departmental workshops, seminars, and tech talks connecting students with current research, emerging technologies, and professional expertise.

This rich blend of practical computing experience, mathematical insight, and access to modern facilities equips students with the skills to thrive in careers in software development, data science, systems design, and beyond.

Progression & Future Opportunities

Graduates combine deep technical computing skills with strong mathematical reasoning, making them highly attractive to employers across tech, finance, data and innovation sectors. They can progress into roles such as software engineer, data scientist, cyber security analyst, or AI specialist with confidence and real‑world readiness:

Career Support Services: The University’s Careers Service and the Department of Mathematics provide tailored support, including one‑to‑one advising, CV and interview workshops, employer networking events, and guidance throughout the degree to help students build clear career pathways.
Employment Outcomes: Graduates are in particularly high demand, with many securing highly skilled positions across technology, analytics, finance and research soon after graduating. On average, Computer Science graduates from Manchester report early‑career earnings around £40,000 within 15 months of finishing their degree.
Industry Engagement: Students benefit from employer engagement events, careers fairs and recruitment activities that bring companies from sectors such as software, gaming, finance, cloud computing and tech consultancy to campus, helping them build professional networks.
University–Industry Recognition: Manchester graduates are targeted by leading employers including global tech, finance and engineering firms, reflecting the combined strength of mathematical and computing training.
Graduate Destinations: Alumni go on to professional roles such as software development, data analytics, cybersecurity, cloud architecture, AI engineering and risk modelling across diverse sectors including technology, finance, gaming and public services.

Further Academic Progression:
Graduates are well positioned to continue into postgraduate study, including specialised master’s degrees such as MSc Artificial Intelligence, MSc Data Science, MSc Cyber Security or other related programmes. They may also pursue research degrees (MPhil/PhD) in areas like Machine Learning, Applied Mathematics or Theoretical Computer Science, further expanding expertise and career opportunities.