School of Engineering, Computing and Mathematics

BSc (Hons) Mathematics

Whether you are drawn to it because of the exhilaration of solving problems, the beauty of an elegant or unexpected result, or its power and adaptability to model the world around us, studying mathematics at Plymouth trains you to think both systematically and creatively. These are skills that are valued in today’s economy and mathematics graduates are sought after by a wide range of employers.

Mathematical sciences degrees

This is one of the suite of mathematics undergraduate degrees that we offer. You can find out more about the various options at the link below.

Opportunities available...

  • A scholarship scheme is available: for more information, see the 'Fees, costs and funding' section, below.

Careers with this subject

A Plymouth Mathematics degree opens the door to a rewarding career in many sectors including science, engineering, finance, government, medicine and education. Employers value work experience, and we offer a varied programme of student placements. Our graduates progress to a wide range of interesting jobs or postgraduate study. Recent employers include KPMG, GCHQ, Lloyds Banking Group, the Met Office, Oxford Clinical Trials Research Unit, and Siemens.

Key features

  • 94% of University of Plymouth Mathematics students think the course prepares them with skills for the future (National Student Survey 2023).
  • This course offers modules in all key areas of mathematics, statistics and theoretical physics, including a wide choice of final-year options. This allows you to follow your interests and shape your future career. 
  • You will acquire skills which are highly sought after by employers: problem-solving skills, knowledge of computing languages and mathematical software packages as well as presentation and communication skills. 
  • Enjoy new facilities – state-of-the-art lecture theatres, computer laboratories, study and social spaces – in our £50 million teaching and research building that opened in 2023. 
  • Benefit from being part of the close-knit, collaborative and supportive family that is Mathematical Sciences at Plymouth. This includes small group tutorials, study space next to staff offices, our lecturers’ open-door policy, student-led learning sessions and the Maths Society.
  • Meet the mathematics of sustainability and climate change in our Mathematics of Planet Earth module.
  • An optional but recommended paid placement year primes you for the career you want. Students who have taken a placement tend to attract multiple job offers.
  • You have an opportunity in the final year to carry out an in-depth research project on a mathematical topic of your choice, supervised by an expert in that field. This involves producing a 50-page report and presenting your work at a poster session.

Course details

  • Year 1

  • Learn the underlying mathematics that underpins the rest of your degree and master coding in the industrial software Python, right from the start. You’ll begin by building on the mathematical skills and topics you learnt at school, studying six core modules including calculus, linear algebra, numerical methods, pure mathematics, and probability. We’ve structured the curriculum so that all of our students acquire a common mathematical expertise, so you’ll also have the flexibility to move between courses as you progress.

    Core modules

    • Stage 1 Mathematics Placement Preparation (BPIE113)

      The route to graduate-level employment is found easier with experience. These sessions are designed to assist students in their search for a year-long placement and in their preparation for the placement itself. Such placements are optional but strongly recommended.

    • Calculus (MATH1702)

      Calculus underpins mathematical modelling in science, finance and industry. This module gives students the ability to calculate accurately and efficiently. Key results are proven and calculus is extended to higher dimensions through partial differentiation and multiple integration. The methods covered in this module will be used by students throughout the rest of their degree.

    • Analysis and Group Theory (MATH1704)

      In this module we explore two fundamental areas of pure mathematics. Analysis provides a rigorous foundation of calculus, while group theory introduces important algebraic structures that are used in many branches of pure mathematics and their applications. A rigorous approach will be taken in both topics, with emphasis on proof. Python will be used to illustrate and investigate cutting edge applications.

    • Mathematical Reasoning (MATH1701)

      This module will introduce the basic reasoning skills needed for the development and applications of modern mathematics. It also introduces Python as a new tool for exploring and applying mathematics to real world problems. The importance of logical thinking will be investigated in various mathematical topics. This will include fundamental properties of prime numbers, their random generation and use in cryptography.

    • Linear Algebra (MATH1703)

      Vectors and matrices are fundamental in mathematics, and central to its applications in statistics, physics, data science, and engineering. This module develops practical skills in handling vectors and matrices, explores the mathematical structure of linear spaces, and elucidates their deep connections with analytic geometry.

    • Probability (MATH1705)

      An understanding of uncertainty and random phenomena is becoming increasingly important in daily life and in the modern workplace. The aim of this module is to develop the concept of chance in a mathematical framework. Random variables are introduced, with examples involving some common distributions, and the concepts of expectation, variance and correlation are investigated using mathematical tools.

    • Numerical Methods (MATH1706)

      In mathematics, solving most real world problems requires the use of computers. This module introduces computational mathematics and algorithms . Students will use mathematical software interactively and write programs in Python. The numerical methods which underlie industrial, scientific and financial applications will be studied.

  • Year 2

  • In Year 2 you'll expand your knowledge with topics including vector calculus, complex analysis, differential equations, transform theory, algebra and mathematical statistics. You will also have a case study-based introduction to operational research, the branch of mathematics developed for better management and decision making, and powerful Monte Carlo methods for simulating complex problems.

    Core modules

    • Stage 2 Mathematics Placement Preparation (BPIE213)

      These sessions are designed to help students obtain a year-long placement in the third year of their programme. Students are assisted both in their search for a placement and in their preparation for the placement itself.

    • Advanced Calculus (MATH2701)

      In this module the geometrical and dynamical concepts needed to describe higher-dimensional objects are introduced. This includes vector calculus techniques and new forms of integration, such as line integration. Students also explore the relationships between integration and differentiation in higher dimensions. We apply advanced calculus to problems from areas such as mechanics and electromagnetism.

    • Statistical Inference and Regression (MATH2702)

      This module provides a mathematical treatment of statistical methods for learning from the data abounding in the modern world. Confidence intervals and hypothesis testing are studied. Methods of estimation are explored, focusing on the maximum likelihood method. The module demonstrates the underlying theory of the general linear model. Applications are implemented using the professional statistical software, R.

    • Differential Equations (MATH2704)

      Differential equations are used to describe changes in nature. This module introduces methods to find exact solutions to ordinary differential equations, and numerical solutions to ordinary and partial differential equations. Extensive use will be made of computational tools. The behaviour of higher dimensional systems will be analysed using the theory of continuous dynamical systems.

    • Operational Research (MATH2705)

      This module gives students the opportunity to work on open-ended case studies in Operational Research (OR) and Monte Carlo methods, both of which play an important role in many areas of industry and finance. Students work both on their own and in teams to develop expertise in Operational Research and programming. They will refine their presentation and communication skills, so enhancing their employability.

    Optional modules

    • Algebra and Transforms (MATH2703)

      This module introduces mathematical structures called rings and fields, which capture properties of objects such as integers, real numbers or polynomials. These structures are used to explore error-correcting codes for data transmission. Calculus is used to introduce Laplace and Fourier transforms, and Fourier series. They are applied to solve differential equations and uncover identities involving irrational numbers.

    • Complex Analysis and Vector Calculus (MATH2706)

      This module explores fundamental relationships between dimensionality and integration. Vector integration theorems for circulation, vorticity and divergence are introduced and vector calculus is applied to real-world examples, such as classical mechanics and orbital dynamics. The mathematics of complex numbers and functions are studied, revealing deep results with applications throughout mathematics.

    • Financial Institutions and Markets (ACF5002)

      This module deals with financial markets, instruments, and institutions. You will examine the bond market, the stock market and the foreign exchange market and explore investment banking and mutual funds.

    • Learning Matters (EDST518)

      A module that builds students’ capacity to recognise and evaluate learning as it occurs in educational, work and recreational settings. It draws upon established, current and critical theory on learning and human development, and focuses on applying these theories to examples of educational practice from existing research and the students’ experiences.

  • Optional placement year

  • You'll have the opportunity to participate in an optional but highly recommended placement year, providing valuable paid professional experience and helping make your CV stand out. Typically students are paid around £17,000 and placement providers have included the Department for Communities and Local Government, Fujitsu, GSK, Vauxhall Motors, VirginCare, Visteon and Jagex Games Studio.

    Optional modules

    • Mathematics and Statistics Placement (BPIE331)

      A 48-week period of professional training is spent as the third year of a sandwich programme while undertaking an approved placement with a suitable company. This provides an opportunity for the student to gain experience of how mathematics is used in a working environment, to consolidate their previous study and to prepare for the final year and employment after graduation. Recent placement providers include GSK, the Office for National Statistics, NATS (air traffic control) and VW Group.

  • Final year

  • Choose from a wide range of modules covering pure and applied mathematics, and operational research, as well as theoretical physics and statistics. A choice of small group case studies and the additional option of an individual project offer you the chance to study an interest in depth. You may opt to study a school-based placement module.

    Optional modules

    • Machine Learning (COMP3003)

      This module introduces machine learning, covering unsupervised, supervised and reinforcement learning from a Bayesian perspective. This includes theory behind a range of learning techniques and how to apply these representations of data in systems that make decisions and predictions.

    • Big Data Analytics (COMP3008)

      The key objective of this module is to familiarise the students with the most important information technologies used in manipulating, storing and analysing big data. Students will work with semi-structured datasets and choose appropriate storage structures for them. A representative of recent non-relational trends is presented—namely, graph-oriented databases.

    • Partial Differential Equations (MATH3701)

      This module deepens students’ understanding of partial differential equations and applies them to real world problems. It provides a variety of analytic and numerical methods for their solution. It includes a wide range of applications such as transport, heat diffusion, wave propagation and nonlinear phenomena.

    • Statistical Data Modelling (MATH3702)

      We study statistical models, including regression and the general and generalised linear models. We estimate model parameters in the classical and Bayesian inference frameworks, using R and Stan software. We describe related computer techniques, including computational matrix algebra and Markov chain Monte Carlo algorithms. We work with multiple data sources using state-of-the art data handling tools.

    • Financial Statistics (MATH3703)

      This module introduces students to financial time series analysis and modelling, illustrated using a variety of applications from the finance industry. We study univariate and multivariate time series models, as well as inferential techniques. Model selection, forecasting and 'curse of dimensionality' problems are treated from both a methodological and a computational point of view.

    • Fluid Dynamics (MATH3704)

      In this module, students will learn how to use mathematics to model a variety of fluid flows. Fluid flow problems are described mathematically as ordinary or partial differential equations. These equations are then solved and the results interpreted for a mixture of theoretical and practical examples of both inviscid and viscous fluid flows. Applications from environmental and industrial modelling will be studied.

    • Quantum Computing (MATH3705)

      Quantum mechanics describes physical systems at the atomic and molecular scale. This allows properties of matter and its interactions with light to be modelled, and these models underpin the rapid development of quantum technologies. This module introduces the principles of quantum mechanics and applies them to quantum computing. Students will study quantum algorithms and techniques to program quantum computers.

    • Industrial Placement (MATH3706)

      This module provides an opportunity for final year students to gain experience of applying mathematics in a professional environment. Students can carry out a placement in a wide variety of areas, including data science, finance, management, research, and software development. As part of this, they develop a range of skills that considerably increase future employment opportunities.

    • Relativity and Cosmology (MATH3707)

      This module introduces the basic concepts of special and general relativity, such as the Lorentz transformations, time dilation, and the curvature of space-time. These ideas help students to understand the basic concepts of modern cosmology, including the standard model of the expanding universe (FLRW model) and its extensions using dark matter and dark energy.

    • Modelling and Numerical Simulation (MATH3708)

      Simulations and modelling are crucial tools that support industrial research and innovation. Students will learn to analyse mathematical models and develop programs to solve them. They will investigate algorithms and discuss their performance. Students will code and run numerical programs on a high performance computer. These forward-looking skills are highly sought after by many employers.

    • Optimisation, Networks and Graphs (MATH3709)

      Optimisation and graph theory are related branches of mathematics with applications in areas as diverse as computer science and logistics. Graphs are used to capture relationships between objects, while optimisation studies algorithms that search for optimal solutions. This module provides both the theory and modern algorithms, including those used in artificial intelligence, required to solve a broad range of problems.

    • Medical Statistics (MATH3710)

      This module equips students with the skills to plan and analyse clinical trials, including crossover and sequential designs, and to perform sample size calculations. The principles of meta-analysis are introduced. Epidemiology is studied, including case-control and cohort studies. Survival analysis is covered in detail. Students gain experience with computer packages that are used in health and medicine.

    • Mathematics of Planet Earth (MATH3712)

      Students work in small groups to research problems directly related to sustainability and the protection of the environment, so addressing some of the most serious problems faced by humanity. This can involve the solution of mathematical, statistical, computational, industrial or economic problems, or challenges in renewable energy engineering. Students present their conclusions orally and in a professional report.

    • Project (MATH3713)

      In this module, students perform individual independent research into a topic in Mathematical Sciences, or Mathematics Education. Students choose a subject to explore in depth, which they are particularly interested in, and receive regular advice and feedback from an expert supervisor. The outputs of the project are a dissertation and a presentation. This module is an ideal preparation for progressing to further study.

    • School Placement (MATH3714)

      This module provides an opportunity for final year students to gain experience in teaching and to develop their key educational skills by working in a school environment for one morning a week over both semesters. Students typically progress from assisting in the classroom to teaching a starter activity over the academic year.

    • Algebraic Geometry and Cryptography (MATH3711)

      Algebraic geometry is a cutting-edge branch of mathematics that links the study of geometric objects to the solution of polynomial equations. This module introduces basic concepts of algebraic geometry and algebraic curves. It applies these ideas to elliptic curve cryptography, an encryption method widely used in today’s world. The encryption techniques that we explore are implemented using Python.

Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

The following programme specification represents the latest course structure and may be subject to change:

BSc Mathematics Programme Specification September 2024 0153

The modules shown for this course are those currently being studied by our students, or are proposed new modules. Please note that programme structures and individual modules are subject to amendment from time to time as part of the University’s curriculum enrichment programme and in line with changes in the University’s policies and requirements.

Entry requirements

UCAS tariff

112 - 128

A level
112-128 points, to include a minimum of 2 A levels, including B in Mathematics or Further Mathematics. (Pure Maths, Pure and Applied Maths, Maths and Statistics, Maths and Mechanics are also accepted as they are considered the same as the Maths A Level). Excluding General Studies. Must have GCSE English and Maths at Grade C/4 or above.
A typical offer might be 120.
We do not run an unconditional offer scheme but may make personalised, lower offers to selected candidates.
Furthermore, applicants attending one of our spring offer holder days may also be given a lower offer after we have met you on the day.
18 Unit BTEC National Diploma/QCF Extended Diploma: DDM to include a distinction in a mathematics unit: individual interview/diagnostic test will be required.
BTEC National Diploma modules
If you hold a BTEC qualification it is vital that you provide our Admissions team with details of the exact modules you have studied as part of the BTEC. This information enables us to process your application quickly and avoid delays in the progress of your application to study with us. Please explicitly state the full list of modules within your qualification at the time of application.
Pass Access to HE Diploma (e.g mathematics, science, combined) with at least 33 credits at merit and/or distinction and to include at least 12 credits in mathematics units with merit. Individual interview/diagnostic test will be required please contact further information.
International Baccalaureate
30 overall to include 5 at Higher Level mathematics.
Other qualifications are also welcome and will be considered individually, as will be individuals returning to education, email
Students may also apply for the BSc (Hons) Mathematics with Foundation Year. Successful completion of the foundation year guarantees automatic progression to the first year of any of our mathematics courses.
We welcome applicants with international qualifications. To view other accepted qualifications please refer to our tariff glossary. 

Fees, costs and funding

Student 2023-2024 2024-2025
Home £9,250 £9,250
International £16,300 £18,100
Part time (Home) £770 £770
Full time fees shown are per annum. Part time fees shown are per 10 credits. Please note that fees are reviewed on an annual basis. Fees and the conditions that apply to them shown in the prospectus are correct at the time of going to print. Fees shown on the web are the most up to date but are still subject to change in exceptional circumstances. More information about fees and funding.

Undergraduate scholarships for international students

To reward outstanding achievement the University of Plymouth offers scholarship schemes to help towards funding your studies.

Additional costs

This course is delivered by the Faculty of Science and Engineering and more details of any additional costs associated with the faculty's courses are listed on the following page: Additional fieldwork and equipment costs.

Tuition fees for optional placement years

The fee for all undergraduate students completing any part of their placement year in the UK in 2023/2024 is £1,850.
The fee for all undergraduate students completing their whole placement year outside the UK in 2023/2024 is £1,385.
Learn more about placement year tuition fees

How to apply

All applications for undergraduate courses are made through UCAS (Universities and Colleges Admissions Service). 
UCAS will ask for the information contained in the box at the top of this course page including the UCAS course code and the institution code. 
To apply for this course and for more information about submitting an application including application deadline dates, please visit the UCAS website.
Support is also available to overseas students applying to the University from our International Office via our how to apply webpage or email

Progression routes

International progression routes

The University of Plymouth International College (UPIC) offers foundation, first-year and pre-masters programmes that lead to University of Plymouth degrees. Courses are specially designed for EU and international students who are missing the grades for direct entry to the University, and include full duration visa sponsorship. You can start in January, May or September, benefitting from small class sizes, top-quality tuition and 24/7 student support.
Find out more at or contact our team at


Meet our school technical staff 

Our technical staff are integral to the delivery of all our programmes and bring a diverse range of expertise and skills to support students in laboratories and workshops.

Discover mathematics at Plymouth

Explore profound and beautiful ideas and understand how they can be applied to the key challenges facing us today and tomorrow.

Our Maths Lab is a dedicated space for students to solve problems, practise presentations and talk about mathematics

Studying mathematics
This research-led mathematics degree equips you with a solid base in pure and applied mathematics.

Welcome to mathematics and statistics at University of Plymouth

Supporting you to succeed
You are supported by an open door policy, a personal tutor system, peer assisted learning and much more.

Studying mathematics at Plymouth
This short film will help you discover what studying one of the range of mathematics degrees at Plymouth is like.

Choose Plymouth

Exciting career opportunities, passionate academics and state-of-the-art facilities

Opening doors with mathematics
Graduating with a mathematics degree can open the door to many employment opportunities, learn how Plymouth can help you stand out from the crowd.

Nathan Broomhead

The truth and perfection of mathematics
To those who have studied it, mathematics is like a language. A language that allows complex ideas to be expressed with precision and clarity.

Exterior of Babbage Building

Babbage Building: where engineering meets design
A state-of-the-art space to inspire creativity and collaboration on our campus.

Advice on personal statements

"Your personal statement should paint a picture of why you want to study mathematics — use it to show me your enthusiasm for the subject. For example, tell me which topics have particularly excited you, and why."
"Outside interests and work experience can show more about you – have you been a trusted person at work? Have you volunteered to help others learn at school? Have you trained people in a sport? Any of these things makes you a stronger applicant, so do mention them, but remember to keep the focus on your studies."
Equations in the mathematics laboratory
Callum Patmore – BSc (Hons) Mathematics

Student profile: Callum Patmore

I would highly recommend taking a mathematics degree as it opens your eyes to the language of the universe and how things truly work. 
The most important factor to any student's journey is having lecturers that positively love the subject they teach. Plymouth provides this in so many ways. In the last year of my degree, I undertook a project on the applications of quantum entanglement. I delved into quantum cryptography and used a method called Schmidt decomposition to determine if a state in quantum mechanics is entangled. My project supervisor was Professor David McMullan and he was the greatest, helping me academically and personally through the ups and downs of the final year of my studies. I truly couldn’t have finished the last year without his guidance. Going forward from my degree at Plymouth I am looking into a career as a mathematics educator. 

Develop your skills, knowledge and confidence with a work placement

Katie Hardman – industrial experience to a job offer
"I found that the skills I had already gained at the University prepared me well for the experience and also for future jobs."
After her industrial internship with Babcock, Katie was offered a full-time graduate position by them after the completion of her degree. Read Katie's story.
Katie Hardman, BSc (Hons) Mathematics student at the University
*These are the latest results from the National Student Survey. Please note that the data published on Discover Uniis updated annually in September.