BSc Hons Mathematical Sciences

3 Years On Campus Bachelors Program

London Metropolitan University

Program Overview

This programme offers a broad and flexible grounding in mathematics, allowing students to build knowledge in core mathematical theory as well as applied areas such as statistics, coding, finance and modelling. It suits students who enjoy problem‑solving, logical thinking and wish to develop strong analytical, IT and research skills that can be applied across many sectors.

Curriculum structure:

Year 1
In the first year, the student develops a firm foundation in mathematical reasoning, proof techniques, and basic computational tools. They study modules such as Mathematical Proofs (introducing rigorous proof techniques and the history of mathematics), Logic and Mathematical Techniques (covering set theory, relations/functions, basic calculus, algebra), and IT for Mathematics plus MAPLE Programming, equipping them with computational and software skills. They also explore Data Analysis, Graph Theory, and Financial Mathematics — gaining early exposure to statistics, discrete mathematics, and finance‑related applications.

Year 2
In the second year, the student delves deeper into both pure and applied mathematics. Core modules like Algebra and Differential Equations deepen their understanding of linear algebra, complex numbers, matrices, and the analytic techniques for dealing with change. Alongside, modules such as Further Mathematical Techniques, Computational Mathematics (optional), Group Theory and Vector Spaces (optional), and Statistical Methods and Modelling Markets (optional) allow them to build versatile skills in modelling, numerical methods, abstract algebra, vectors/spaces and statistical modelling for finance or economics.

Year 3
In the final year, the student undertakes an Academic Independent Study — a self‑guided project under faculty supervision, allowing them to explore a mathematical topic of individual interest, culminating in a written report and presentation. They also take Mathematical Modelling and Integral and Vector Calculus (core), deepening their ability to model real‑world problems and work with multivariable/vector calculus. Optional advanced modules such as Cryptography and Number Theory, Error Correcting Codes, Financial Modelling and Forecasting, Category Theory, Analysis, and Mathematics of Infinity enable specialisation in areas ranging from pure mathematics and abstract theory to finance‑oriented and computational topics.

Focus areas:
The programme covers foundational mathematics (algebra, calculus, logic), computational and programming skills (using tools like MAPLE), statistics and data analysis, applied mathematics (modelling, financial mathematics), and specialized electives such as cryptography, coding theory, number theory, vector spaces, and advanced analysis.

Learning outcomes:
Students will graduate with strong mathematical reasoning, proof-writing and abstract thinking skills, competence in statistical and data analysis, proficiency in mathematical software and programming, and the ability to model and solve real-world problems using mathematical techniques. They will also have the flexibility to specialise in pure mathematics, finance‑oriented mathematics, cryptography, or applied modelling.

Professional alignment (accreditation):
The course is accredited by the Institute of Mathematics and its Applications (IMA), meeting in part the educational requirements for chartered status.

Reputation (employability rankings):
The mathematics‑related courses at London Met have achieved excellent student satisfaction ratings, and past graduates have secured roles such as analysts, financial advisors, researchers, or moved on to postgraduate studies — including teaching (PGCE) or specialised quantitative careers.

Experiential Learning (Research, Projects, Internships etc.)

At London Met, students on the BSc (Hons) Mathematical Sciences programme don’t just learn abstract maths — they actively build real-world quantitative, computational, and analytical skills. They get access to well-equipped computer labs with professional software and benefit from a curriculum that emphasises applied mathematics, data analysis, modelling, and IT tools — all of which prepare them for practical, workplace-relevant tasks.

Specifically:

Use of specialised software: In modules such as Data Analysis, students work with tools like Excel, SPSS, and R to analyse real datasets and draw meaningful conclusions.
Programming and computational tools: Through a module like MAPLE Programming, students gain experience with algebraic software used for solving complex mathematical problems.
Group-based problem solving and modelling: In modules such as Mathematical Modelling, students collaboratively tackle real-life problems — modelling physical, industrial, or business situations, constructing mathematical models (differential equations, difference equations), analysing these models (analytically or numerically), and presenting their findings via reports and presentations.
Independent research opportunity: The Academic Independent Study module in the final year allows students to explore a topic of their own interest under staff supervision.
Career-oriented work exposure: The Career Development Learning module enables students to engage in placements, volunteering, work-based learning, or research-related activity — helping them build professional experience, networks, and a personal portfolio before graduation.

In addition to these, students enjoy access to the University’s extensive IT and library facilities: PCs, Macs, specialised mathematics/statistics software, hundreds of computer-workstations across labs, and robust library resources for study and research.

Course Structure & Academic Breadth

Here’s what the programme involves over the years:

In the initial years, foundational mathematics: calculus, linear algebra, mathematical proofs, logic, and mathematical techniques.
Core computational and data-oriented modules: IT for Mathematics, MAPLE Programming, Data Analysis.
As the degree progresses, options to specialise — for instance in financial mathematics, cryptography & number theory, coding theory (error-correcting codes), advanced analysis, mathematical modelling, and even abstract areas like the mathematics of infinity.
Flexibility in tailoring studies according to interests — whether one is drawn to pure mathematics, statistics, finance, cryptography, modelling, or computational maths.

Facilities
Students have access to:

Computer labs with specialised mathematics and statistical software.
Library facilities with extensive digital and print resources.
Research supervision and project guidance for independent study modules.
Career support and placement opportunities within the university.

Progression & Future Opportunities

The BSc (Hons) Mathematical Sciences at London Metropolitan University prepares graduates to enter roles such as data analyst, financial analyst, operational researcher, or secondary‑school mathematics teacher. Upon graduation, they will have developed strong quantitative, statistical, modelling, and IT‑based skills that are in demand across finance, tech, education, and business sectors:

The course carries accreditation from the Institute of Mathematics and its Applications (IMA), meaning it meets (in part) the educational requirements for chartered status — a long‑term professional credential recognised by employers.
95% of graduates go on to work and/or study 15 months after completing the course.
Average earnings are around £26,500 three years after graduation.
After five years, typical salaries rise, with median earnings around £40,500 (range ~£30,500–£55,000) depending on sector and role.
University–industry relevance: Through modules like financial mathematics, statistical modelling, mathematical modelling, and data analysis, students build practical skills that employers in finance, analytics, and IT actively seek.
On‑campus support: The course offers a “Career Development Learning” module in the final year, where students can undertake real‑world professional activities such as placements, volunteering, or projects to build experience and networks before graduating.

Further Academic Progression:
The degree also serves as an excellent springboard for postgraduate studies. Graduates may pursue a master’s in fields like applied mathematics, data science, statistics, or financial mathematics. Alternatively, they could opt for teacher training, such as a PGCE in Secondary Mathematics Teaching, or other advanced professional qualifications, with the IMA‑accredited degree providing a solid foundational qualification recognised by professional bodies.