Mathematics with Computing with Industrial Experience BSc (Hons)

4 Years On Campus Bachelors Program

Queen Mary University of London

Program Overview

The Mathematics with Computing with Industrial Experience BSc (Hons) at Queen Mary University of London combines strong mathematical foundations with practical computing skills, preparing students to solve complex problems and develop real software solutions. It is perfect for those who enjoy both numbers and coding, offering an industrial placement year that gives valuable professional experience and a competitive edge in careers like technology, data science, and finance.

Curriculum Structure

Year 1:
The first year focuses on core mathematical and computing skills through modules such as Introduction to Analysis with Calculus, Vectors and Matrices, Probability & Statistics, and Programming in Python I. Students develop logical thinking, problem-solving abilities, and initial coding skills that form the foundation for more advanced study.

Year 2:
The second year builds deeper knowledge with compulsory modules including Data Structures and Algorithms, Differential Equations, Linear Algebra I, and Probability and Statistics II. Professional Skills for Mathematicians prepares students for teamwork, communication, and workplace readiness, while optional modules like Statistical Modelling or Game Theory allow specialization.

Year 3 – Industrial Experience:
Year 3 is a professional placement year, giving students hands-on experience in a real workplace. This industrial experience enables them to apply mathematical and computing knowledge in contexts such as software development, data analysis, and systems modelling, building skills highly valued by employers.

Final Year (Year 4):
The final year focuses on advanced study through modules like Numerical Computing with C and C++, a Mathematics with Computing Project, and optional topics such as Deep Learning, Algorithmic Graph Theory, or Machine Learning. Students complete high-level projects demonstrating independence, technical expertise, and creative problem-solving.

Focus areas (in a string):

Calculus, Linear Algebra, Probability & Statistics, Python Programming, Data Structures & Algorithms, Numerical Computing, Machine Learning, Artificial Intelligence, Project Work

Learning outcomes (in a string):

Develop advanced mathematical reasoning, apply computing and algorithmic thinking to real problems, gain professional workplace experience, communicate computational solutions effectively, and design and implement high-quality software systems

Professional alignment (accreditation):

The programme includes an industrial experience year, ensuring graduates leave with both academic depth and practical industry-aligned skills that employers seek.

Reputation (employability rankings):

Queen Mary’s School of Mathematical Sciences is highly regarded in the UK and globally, with around 90% of graduates progressing to work or further study shortly after completing their degree.

Experiential Learning (Research, Projects, Internships etc.)

At Queen Mary University of London, the Mathematics with Computing with Industrial Experience BSc (Hons) degree is designed to develop real-world mathematical and computational skills. The programme combines deep mathematical theory with practical computing expertise, allowing students to work on problem-solving tasks that mirror professional challenges. Students on the industrial experience route spend a full year working with an employer, gaining valuable workplace experience, building professional networks, and enhancing their career readiness before graduation.

The programme is supported by excellent campus facilities, including the Informatics Teaching Laboratory, which provides modern programming labs, high-performance computing resources, and collaborative spaces designed for group projects and applied learning.

Here’s how experiential learning is integrated into the course:

Real programming practice: Students work with languages such as Python, C, and C++ in modules covering numerical computing, algorithms, and machine learning, applying skills to real-world problems.
Professional software environments: Access to specialist labs offers industry-standard tools and development platforms for coding, testing, and collaborative workflows.
Industrial experience year: In the third year of the four-year programme, students complete a professional placement, gaining practical work experience in computing, data analytics, finance, technology, or engineering.
Project-based learning: A substantial final-year project allows students to apply mathematical modelling and computational skills to a complex problem of their choice.
Collaborative study spaces: Dedicated labs and study areas encourage teamwork and peer-to-peer learning for assignments and projects.
Career-focused support: The university provides employability guidance, including preparation for internships, placements, graduate schemes, and job applications throughout the degree.

Progression & Future Opportunities

Graduates from the Mathematics with Computing with Industrial Experience BSc (Hons) at Queen Mary University of London are well‑placed to enter analytical and tech‑driven careers, with most alumni in employment or further study shortly after graduating and strong support from careers services to help launch their professional journey: a typical destination includes roles in data analysis, software development, quantitative research and systems engineering.⁴⁄ᵒ⁾ Nearly 90–93% of graduates go into work or further study within 15 months of finishing their degree, highlighting the real value employers place on this blend of mathematics and computing skills.⁴⁄ᵃ⁾ Typical job roles include:

Data Analyst / Quantitative Analyst – interpreting complex datasets and models.
Software Developer / Systems Engineer – building and testing efficient software solutions.
Technology Consultant / Business Analyst – advising organisations on tech‑led strategy.
Research Assistant / Graduate Developer – applying computational and mathematical methods to innovation problems.

Here’s how Queen Mary helps you move into these roles:

University‑led careers support: Dedicated Careers & Enterprise services offer CV and interview preparation, networking events, job boards and workshops to help you plan and secure internships, placements and graduate roles.⁵⁄¹⁾
School‑specific support: The School of Mathematical Sciences careers team provides subject‑focused guidance on employability, industry trends, internship applications and skills certification, with recruiter engagement and employer‑led events to boost your professional profile.⁰⁄¹⁾
Industrial experience year: The four‑year degree includes a year in industry where you work in real professional settings, giving you hands‑on experience that strengthens your CV and helps you build industry contacts while still studying.⁰⁄¹⁾
Graduate outcomes: Most graduates are working or continuing study shortly after finishing, a strong indicator of the degree’s relevance across sectors such as finance, tech, analytics and consulting.⁰⁄¹⁾
Reputation and value: Queen Mary is a well‑regarded research‑intensive university with solid academic standing in mathematics and computing disciplines, enhancing the long‑term credibility of your qualification.¹⁹⁾

Further Academic Progression:
After completing this BSc, students have excellent pathways into postgraduate and specialised study. You could pursue master’s degrees in areas such as Data Science, Artificial Intelligence and Machine Learning, Applied Mathematics, Financial Mathematics or Computer Science, building deeper technical expertise. For those aiming at research or academic careers, progressing to MRes or PhD study is a strong next step. Alternatively, if your goal is professional or sector‑specific advancement, specialised postgraduate qualifications in Cybersecurity, Software Engineering or Business Analytics can further elevate your career prospects.