BSc Computer Science and Mathematics with Industrial Experience

4 Years On Campus Bachelors Program

University of Manchester

Program Overview

This four‑year joint honours degree combines in‑depth study of computer science and mathematics with a full year of industrial work experience, giving students a powerful blend of academic knowledge and practical skills that employers value. It suits motivated learners who want the analytical foundations of mathematics alongside cutting‑edge computing expertise, and who are eager to gain real‑world experience before graduation.

Curriculum Structure:

Year 1:
In the first year, students build a solid grounding in both disciplines, studying fundamental computing topics like Introduction to Programming 1 and Introduction to Programming 2 alongside mathematics units such as Linear Algebra, Mathematical Foundations and Analysis, Probability I and Mathematical Techniques for Computer Science. These courses develop core programming abilities, logical thinking, problem‑solving and quantitative reasoning — the pillars of both computer science and mathematics.

Year 2:
The second year deepens both mathematical and computing expertise with a mix of compulsory and optional modules. Students typically explore more advanced topics in algorithms, data structures, systems and mathematical modelling, while continuing to refine their analytical skills across probability, statistics and abstract mathematics. This year prepares learners to apply computational logic and mathematical insight to a wider range of complex problems.

Industrial Experience Year (Year 3):
Between Years 2 and 4, students undertake a one‑year industrial placement, working in a professional environment where they apply their academic learning to real projects, build practical skills, and gain valuable workplace experience. This year gives them an edge in the job market by helping them develop confidence, professional networks and a clearer sense of career direction.

Year 4:
In the final academic year, learners return to campus to specialise further, choosing advanced computing options such as AI and Games, Natural Language Processing, Algorithms and Complexity alongside mathematical choices like Mathematical Systems and Computation and Multivariate Statistics and Machine Learning. A final‑year project allows them to showcase their combined expertise in a substantial independent or team‑based piece of work.

Focus Areas:
Software development and programming, algorithms and data structures, computational logic, abstract and applied mathematics, statistics and probability, mathematical modelling, and practical industrial experience.

Learning Outcomes:
Graduates emerge with strong computational and mathematical reasoning, an ability to solve complex problems using both disciplines, and real‑world experience that demonstrates professional competence. They develop transferable skills in project work, analytical thinking, software design and quantitative analysis that set them up for success in tech, finance, research or further study.

Professional Alignment (Accreditation):
The programme integrates the academic standards of both the Department of Computer Science and the School of Mathematics, aligning with industry expectations for computing and quantitative roles and preparing students for careers where high‑level analytical and technical skills are essential.

Reputation (Employability Rankings):
The University of Manchester’s computer science provision is ranked among the UK’s top 10, and the institution is one of the most targeted by employers, meaning graduates with this combination of deep academic knowledge and industrial experience are highly sought after across technology, finance, consulting and research sectors.

Experiential Learning (Research, Projects, Internships etc.)

The BSc Computer Science and Mathematics with Industrial Experience programme at The University of Manchester uniquely blends strong mathematical foundations with practical computing skills and a dedicated period of professional experience. From the first year, students develop hands‑on skills in programming labs and practical workshops, applying concepts from algorithms, software development, and mathematical modelling to real tasks. Throughout the degree, students work with modern development environments and specialist mathematical software to solve problems individually and in teams. A key feature of this programme is the industrial experience year, where students spend a full year working within industry, applying both computational and mathematical skills in a professional setting. This experience not only enhances technical ability but also builds communication, teamwork, and workplace confidence — giving students a strong advantage when entering competitive job markets.

Experiential learning includes:

Industrial experience year: A supervised, full‑year work placement in industry where students apply computing and mathematics in real professional contexts, gaining workplace experience and professional networks.
Hands‑on programming labs: Practical laboratory sessions using current languages and tools to develop software, build systems, and solve real technical challenges.
Collaborative project work: Group projects mirror real‑world team settings, helping students build communication and project management skills alongside technical competence.
Mathematical modelling and analysis sessions: Structured activities using specialist software to apply mathematical reasoning to computational and data problems.
Professional development workshops: Dedicated sessions on CV writing, interview preparation, and career planning help students make the most of internship and job opportunities.

Academic Environment & Facilities
Students on the BSc Computer Science and Mathematics with Industrial Experience degree benefit from a dynamic academic environment that supports both computation and mathematics. Key facilities include:

Dedicated computing laboratories equipped with up‑to‑date hardware and development tools used in industry, enabling practical software engineering and system design.
Interactive study spaces and collaborative areas where students work individually or with peers on coding projects, mathematical problems, and research tasks.
Specialist mathematical computing resources that support modelling, algorithm analysis, and quantitative work 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 in both computer science and mathematics.
Departmental workshops, seminars, and industry talks that connect students with current research, emerging technologies, and professional pathways.

This combination of immersive industrial experience, practical lab work, and access to modern facilities prepares students for careers in software development, data science, computational research, and technology leadership roles.

Progression & Future Opportunities

Graduates combine strong computational and mathematical skills with valuable real‑world experience gained during an industrial placement, making them highly attractive to employers in tech, finance and data science. They can progress into roles such as software engineer, data scientist, AI developer, or systems analyst with confidence and practical insight:

Career Support Services: The University’s Careers Service and departmental teams provide tailored support throughout study and the industrial experience year, including personalised advising, CV and interview workshops, employer networking events and placement preparation to help students build career readiness.
Employment Outcomes: Students who complete industrial experience often move directly into graduate roles or return to their placement employer, with many securing highly skilled positions and reporting strong early‑career earning potential compared with peers without work experience.
Industry Engagement: The industrial experience component connects students with real employers in sectors such as technology, finance, engineering and consulting. Events like careers fairs and company‑hosted workshops help build professional networks before graduation.
University–Industry Recognition: Graduates are recognised by leading employers across global tech, finance and analytics fields, reflecting the value of hands‑on experience combined with academic training in mathematics and computing.
Graduate Destinations: Alumni enter professional roles in software development, data analytics, cloud computing, cybersecurity, AI and systems engineering across diverse sectors including technology companies, financial institutions and consultancy firms.

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