School of Engineering, Computing and Mathematics

BSc (Hons) Mathematics with Computer Science

UCAS tariff 112 - 128 Contextual offers
A contextual offer is an offer to study at university that takes personal circumstances that may affect grades into account.
UCAS course code G1I0
Institution code P60
Duration

3 years

(+ optional placement)
Course type

Full-time
Study location Plymouth
Register for open day
Apply at UCAS.com

Combine your passion for mathematics and computer science. The two subjects have common roots stretching back to the dawn of computing, and together have solved some of the most fundamental problems in science and industry. You will explore the beauty of mathematics in familiar areas such as calculus, algebra and probability, taught in a new and inspiring way, and extend your skills into computing-intensive topics such as fluid dynamics, artificial intelligence and high performance computing.

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.

Supporting you to succeed

A supportive environment with great facilities and opportunities to gain work experience.

Why Plymouth is an exciting place to study mathematics
Discover what its like to study mathematics at Plymouth and how it can provide a firm basis for a successful career.

Elizabeth Goult - BSc (Hons) Mathematics

Develop your skills, knowledge and confidence with a work placement
"Applying the technical skills learnt in my degree to real problems has been invaluable".

Exterior of Babbage Building

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

Careers with this subject
Enjoy exceptionally good career prospects.
With research-inspired modules on large-scale simulation and modelling, quantum computing and cryptography, this course sets you up well with cutting-edge skills for the working world. Examples of companies that employ our marketable graduates are: Ipsos MORI, CERN, the Met Office, NATS, and DSTL.
Discover what you can do with a mathematics degree and a computer science degree.

Key features
  • Acquire state-of-the-art mathematical and computing skills that are highly sought after by industry, including machine learning and optimisation.
  • Understand and develop algorithms that are essential for the modern world, while mastering computer programming using languages such as Python and R.
  • Be trained in parallel computing, something rarely offered at undergraduate level, using our campus supercomputer.
  • Be inspired by the research activities of staff – interests include artificial intelligence, large scale simulations, offshore renewable energy, quantum physics and environmental statistics.
  • Enjoy new facilities – state of the art lecture theatres, computer laboratories, study and social spaces – in our £50 million teaching and research building.
  • Core modules are shared with BSc Mathematics, allowing the flexibility of easy transfer to our other mathematics degrees.
  • 100% of our students agreed that staff are good at explaining mathematics in the 2024 National Student Survey.
  • As a graduate of this degree you can exploit the increase in available computing power, which is key to future economic growth and enhances your employability.

Course details

  • Year 1

  • Learn the underlying mathematics that underpins the rest of your degree. Master coding in the industrial software Python, right from the start and apply it in algorithms to solve real-world problems including public key cryptography. 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

    MATH1701
    Mathematical Reasoning 20 credits

    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.

    60% Coursework

    40% Tests

    MATH1702
    Calculus 20 credits

    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.

    60% Examinations

    40% Coursework

    MATH1703
    Linear Algebra 20 credits

    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.

    60% Examinations

    40% Coursework

    MATH1704
    Analysis and Group Theory 20 credits

    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.

    60% Tests

    40% Coursework

    MATH1705
    Probability 20 credits

    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.

    60% Examinations

    40% Coursework

    MATH1706
    Numerical Methods 20 credits

    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.

    60% Examinations

    40% Coursework

  • Year 2

  • In Year 2, you'll expand your rigorous understanding of mathematics, always accompanied by the study of applications. This year also includes topics in artificial intelligence, including evolutionary algorithms and machine learning. Operational research introduces Monte Carlo methods, which rely on randomness and sampling to solve impactful problems.

    Core modules

    BPIE213
    Stage 2 Mathematics Placement Preparation 0 credits

    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.

    COMP2002
    Artificial Intelligence 20 credits

    This module provides students with an introduction to the principles of artificial intelligence and the methods used in that field. Topics covered include search and optimisation, knowledge representation and reasoning, and machine learning. Students will gain experience of modelling and simulation, and will apply analytical tools to evaluating results, and will consider the ethical implications of the introduction of AI.

    100% Coursework

    MATH2701
    Advanced Calculus 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH2702
    Statistical Inference and Regression 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH2703
    Algebra and Transforms 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH2704
    Differential Equations 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH2705
    Operational Research 20 credits

    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.

    75% Coursework

    25% Practicals

  • Year 3

  • 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, GlaxoSmithKline, Vauxhall Motors, VirginCare, Visteon and Jagex Games Studio.
    In your final year, master state-of-the-art topics such as large-scale simulations, machine learning from a Bayesian perspective, and big data. Options include elliptic curve cryptography, quantum computing and optimisation of problems such as wind turbine placement. You also do an individual or group project module, which offers you the chance to study a topic of your choice in depth.

    Core modules

    BPIE331
    Mathematics and Statistics Placement 20 credits

    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.

    80% Coursework

    20% Practicals

  • Final year

  • Core modules

    COMP3003
    Machine Learning 20 credits

    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.

    100% Coursework

    COMP3008
    Big Data Analytics 20 credits

    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.

    100% Coursework

    MATH3708
    Modelling and Numerical Simulation 20 credits

    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.

    100% Coursework

    Optional modules

    MATH3701
    Partial Differential Equations 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH3702
    Statistical Data Modelling 20 credits

    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.

    100% Coursework

    MATH3704
    Fluid Dynamics 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH3705
    Quantum Computing 20 credits

    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.

    50% Coursework

    50% Examinations

    MATH3706
    Industrial Placement 20 credits

    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.

    80% Coursework

    20% Practicals

    MATH3707
    Relativity and Cosmology 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH3709
    Optimisation, Networks and Graphs 20 credits

    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.

    100% Coursework

    MATH3710
    Medical Statistics 20 credits

    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.

    70% Examinations

    30% Coursework

    MATH3712
    Mathematics of Planet Earth 20 credits

    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.

    70% Coursework

    30% Practicals

    MATH3713
    Project 20 credits

    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.

    80% Coursework

    20% Practicals

    MATH3714
    School Placement 20 credits

    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.

    80% Coursework

    20% Practicals

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

Contextual offers: Typically, the contextual offer for this course is 8 points below the advertised tariff. A contextual offer is an offer to study at university that takes into account individual circumstances that are beyond your control, and that can potentially impact your learning and your exam results, or your confidence in applying to university.

Check your eligibility for a contextual offer

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.
We do not run an unconditional offer scheme but may make personalised, lower offers to selected candidates.
BTEC
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.
Access
Pass Access to HE Diploma with 33 level 3 credits with at least 12 Level 3 credits at distinction in Mathematics including a unit introducing calculus, plus, GCSEs: English and Maths at a Grade C/4.
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 maths@plymouth.ac.uk
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
New student 2024-2025 2025-2026 *
Home £9,250 £9,535
International £18,100 £18,650
Part time (Home) £770 £795
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.

* UK Government announcement on tuition fees

On Monday 4 November 2024, the UK Government announced a proposal to increase tuition fees for home undergraduate students from £9,250 to £9,535 per annum from September 2025 onwards. The University of Plymouth intends to apply this new fee from September 2025. However, implementation of this increase will be subject to parliamentary procedure. This change applies to new students starting their studies in September 2025. For current and returning students, the University is reviewing fees and will update you as soon as possible.

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 2024/2025 is £1,850.
The fee for all undergraduate students completing their whole placement year outside the UK in 2024/2025 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 admissions@plymouth.ac.uk.

Study in good company with like-minded people

Maths students doing equations on a clear board
Be part of a close-knit, collaborative and supportive family
With small group tutorials, study space next to staff offices, our lecturers’ open-door policy, student-led learning sessions and the Maths and Computing student societies.
Colourful pink computing, technology and data. Getty images 1271942842.
Underpinned by research
Whether you are interested in cryptography, spotting patterns in large datasets, finding optimal solutions using finite budgets and resources, or using a supercomputer, you can pursue your interests in this course.
Computing students working in a group
Work on cutting edge commercial and scientific applications
Final year projects have included post-quantum cryptography, neural networks, financial portfolio construction, optimal wind turbine placement and medical diagnostics.
Developing programming and coding technologies. Website design. Programmer working in a software develop company office.
Mathematical algorithms and logic are the foundations of computer science
Studying Mathematics in conjunction with Computer Science provides you with a thorough understanding of mathematics and how algorithms work. This will prepare you for a future career in this rapidly growing and changing field.
Student coding
Develop your programming skills
Develop your programming skills on computers and high-performance clusters. The first year will provide you with a solid foundation in Python. As the course progresses, other languages and software are introduced.
Mathematical sciences placement students - hero image
Flexibility across a suite of Mathematics courses
All of our mathematics courses share a common first year. They also permit greater flexibility: as your knowledge and understanding deepens, you are able to follow your interests and, if you wish, transfer to one of our other mathematics degrees.

People

  • Lecturer in Mathematics
    Programme Manager, Applied Mathematician
  • Lecturer in Theoretical Physics
    Mathematical Sciences Employability Lead, Member HPQCD collaboration
  • Lecturer in Data Science/Statistics
    First Year Tutor
  • Lecturer in Statistics
    Mathematical Sciences Employability Lead
  • Head of School and substantive Professor of Mathematics
  • Lecturer in Mathematical Sciences
    Applied Mathematician
  • Lecturer in Pure Mathematics
    Admissions Tutor for Mathematical Sciences
  • Associate Professor in Mathematics
    Pure Mathematician
  • Associate Head of School (UG Education)
    Lead of the Plymouth GPU Research Centre
  • Emeritus Professor
    First Year Tutor, Professor of Theoretical Physics
  • Lecturer in Applied Mathematics/Theoretical Physics
    Foundation Year Programme Manager
  • Associate Professor of Theoretical Physics
    High Performance Computing Unit Director, Associate Member CERN theory group
  • Associate Professor in Theoretical Physics
    Theoretical Physicist, Member User Forum of the UK Central Laser Facility
  • Associate Professor of Theoretical Physics
    Final Year Tutor, Otto Hahn Medal winner
  • Lecturer in Mathematics Education
    Senior Personal Tutor, Mathematics Education Lead
  • Associate Head of School (Resources)
    Programme manager, MSc Health Data Science and Statistics
  • Associate Professor in Mathematics and Statistics
    Senior Fellow of the HE Academy

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.