Mathematics with Computing with Year Abroad BSc (Hons)

4 Years On Campus Bachelors Program

Queen Mary University of London

Program Overview

The Mathematics with Computing with Year Abroad BSc (Hons) at Queen Mary University of London combines the rigorous study of mathematics and computing with a full year abroad at a partner university. It is designed for students who want strong analytical and computational skills along with international academic and cultural experience.

Curriculum structure:

Year 1
The first year provides a solid foundation in mathematics and programming. Students study Introduction to Analysis with Calculus, Numbers, Sets and Functions, Vectors and Matrices, Probability & Statistics, and computing modules such as Object-Oriented Programming and Programming in Python I.

Year 2
The second year deepens knowledge in mathematics and computing. Core modules include Differential Equations, Linear Algebra I, Data Structures and Algorithms, Probability & Statistics II, and Theory of Computing. Students also take Professional Skills for Mathematicians and choose electives such as Complex Variables, Linear Optimisation and Game Theory, or Statistical Modelling I to tailor their learning.

Year 3 (Year Abroad)
In the third year, students study at a partner university abroad, gaining international academic experience and exposure to different teaching styles and cultures. This year abroad enhances global perspective and broadens professional and personal development.

Year 4 (Final Academic Year)
In the final year, students complete the Mathematics with Computing Project, an independent investigation integrating mathematics and computing. Core modules include Numerical Computing with C and C++, with elective options such as Deep Learning, Introduction to Machine Learning, Algorithmic Graph Theory, Computer Graphics, Number Theory, Numerical Analysis, and Random Processes — allowing specialization toward data science, computational mathematics, or theoretical computing.

Focus areas:
Mathematical theory and analysis, programming (Python, C/C++), data structures and algorithms, probability and statistics, numerical computing, computational mathematics, machine learning and data-driven computation, international academic experience.

Learning outcomes:
Graduates develop strong mathematical reasoning, computational problem-solving skills, programming proficiency, the ability to model and analyse complex problems, and gain a global perspective through the year abroad — equipping them for careers in data science, finance, technology, or further study internationally.

Professional alignment (accreditation):
Delivered by the School of Mathematical Sciences at Queen Mary, the programme aligns with academic and professional standards in mathematics and computing, preparing graduates for industry roles and postgraduate study.

Reputation (employability & career prospects):
Graduates gain international exposure and networking opportunities through the year abroad, enhancing employability in global industries such as finance, technology, and data analytics. The programme maintains the same strong mathematics and computing foundation as the standard BSc, ensuring career readiness.

Experiential Learning (Research, Projects, Internships etc.)

The four‑year BSc (Hons) in Mathematics with Computing with a Year Abroad offers all the benefits of the standard Mathematics with Computing degree, plus the opportunity to spend a full academic year at a partner university overseas. This adds a global dimension to the programme, allowing students to experience different academic systems, broaden cultural horizons, and gain international exposure before graduation.

Experiential Learning in the Year Abroad Programme

Students on the Year Abroad track benefit from rigorous mathematics and computing training at QMUL, combined with international study experiences:

Access to dedicated computing labs and teaching facilities in the School of Mathematical Sciences, including modern teaching rooms, private and group study areas, and social spaces.
Use of real programming languages and tools: Python in first-year modules and C/C++ in later years for numerical computing, data structures, algorithms, and computational mathematics.
Completion of a substantial final-year project combining mathematics and computing, with options for individual or small-group work.
Flexible electives such as machine learning, deep learning, computer graphics, coding theory, numerical analysis, complex networks, and number theory.
Exposure to different teaching styles, new computational tools, and an international academic environment during the year abroad.
Continued support from QMUL’s mathematical sciences community, including library access, peer collaboration, student societies, and careers guidance.

Programme Structure (with Year Abroad Option)

Years 1 and 2: Core mathematics and computing modules, including Introduction to Analysis with Calculus, Numbers, Sets and Functions, Object-Oriented Programming, Python, Probability & Statistics, Vectors and Matrices, Data Structures & Algorithms, Linear Algebra, Differential Equations, and Theory of Computing.
Year 3: Study at a partner university abroad, taking courses that complement or enhance mathematical or computing skills and exploring electives unavailable at QMUL.
Year 4 (Final Year): Return to QMUL to complete the final year, including the major Mathematics with Computing project (30 credits), numerical computing with C/C++, and elective modules in areas such as machine learning, coding theory, graphics, and numerical analysis.

Why the Year Abroad Variant Is Especially Compelling

This variant is ideal for students who:

Want to combine strong mathematical and computational training with international exposure.
Are interested in seeing how mathematics and computing are applied in other countries, broadening their perspective and inspiring innovative thinking.
Hope to build cross-cultural skills, international networks, and a competitive edge for global careers in data science, technology, finance, or research.
Value flexibility, maintaining the robust QMUL structure while adding a unique experiential layer.

Progression & Future Opportunities

Graduates of the Mathematics with Computing with Year Abroad BSc (Hons) at Queen Mary University of London (QMUL) are well-prepared for careers such as data analyst or data scientist, quantitative/financial analyst, software or systems engineer, or insights/business analyst. The added international experience enhances their adaptability and global outlook, making them highly competitive for roles in multinational companies and international organisations.

Why This Degree Opens Doors:

University‑supported employability services: The QMUL School of Mathematical Sciences provides careers support including internship coordination, CV and application coaching, interview preparation, and networking events.
Strong employment record & starting salary: Around 90% of graduates are in work or further study within six months of graduation. The typical starting salary is approximately £30,336, with some reports up to £32,000 within 15 months.
Access to industry-leading employers: Graduates have joined top firms such as Accenture, Deloitte, KPMG, J.P. Morgan, Deutsche Bank, and the Bank of England across finance, consultancy, tech, and analytics roles.
Accredited, high‑quality academic training with long-term value: The programme integrates rigorous mathematics (linear algebra, statistics, differential equations) with computing fundamentals (data structures, algorithms, theory of computing), providing a strong foundation for applied and theoretical work.
International exposure and flexibility: The Year Abroad component allows students to gain cultural experience and global perspectives, enhancing employability in international and multinational organisations.
Diverse graduate outcomes: Graduates are equipped for careers in software engineering, data science, finance, statistics, project management, consulting, and actuarial roles.

Further Academic Progression:
After completing the BSc, graduates may continue their studies with Master’s or research programmes in areas such as data science, machine learning, quantitative finance, statistics, computational mathematics, or computer science. They may also pursue professional qualifications in actuarial science, finance, or data analytics, or progress to doctoral studies for advanced research opportunities.