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Mathematics with Computer Science BSc

Key Information

Course code

G1GL

G1GK with placement

Start date

September

Placement available

Mode of study

3 years full-time

4 years full-time with placement

Fees

2024/25

UK £9,250

International £21,260

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Entry requirements

2024/25

ABB - BBC (A-level)

DMM and A-level in Maths or Further Maths at grade B. (BTEC)

29 (IB)

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Overview

Ranked no.4 in London for student satisfaction in mathematics by The Complete University Guide 2024.

The world relies on computers and so do most businesses and organisations. Mathematics is the language of computer science so if you have the skills for both you’ll find a whole range of careers available to you in most sectors.

On this single honours course you’ll develop your mathematical and statistical knowledge and apply these skills to solve problems in computing, business and other areas.

Approximately two-thirds of the course is devoted to mathematical and statistical areas. The mathematics subjects on this course focus particularly on aspects of modern algebra that relate to computer science and also include a considerable amount of numerical analysis of mathematical problems. You have the opportunity to specialise in Level 3 so as an example, you may choose modern encryption methods as used in internet transactions.

Follow the four-year Professional Placement degree programme and you‘ll benefit from our extensive experience in helping students to find well-paid work placements with blue-chip companies. Our sandwich students find that their mathematical, computer science and transferable skills are in demand in many sectors, both in the UK and abroad.

Areas recently offering placements include: accountancy, aviation, banking, defence, finance, insurance, IT (software development, network management and design), management (public and private sector), marketing and telecommunications.

This programme will meet the educational requirements of the Chartered Mathematician designation, awarded by the Institute of Mathematics and its Applications, when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught master's degrees.

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Course content

At Brunel we aim to make your transition into the university style of learning as easy as possible. So in the first few weeks of Level 1 you’ll start your learning in small groups of about 20 students. Approximately two-thirds of the course is devoted to mathematical and statistical subjects and one third to computer science.

An individual piece of course-work will account for one third of Level 3.

You’ll be able to select from a large number of projects covering a wide range of mathematical areas and applications. Your project will be supervised by a staff member. You’ll emphasise real applications or abstract theories, using theoretical and/or computational tools. If you’ve completed a placement you will be able to choose a project associated with your work experience. Examples of project titles are:

  • The very famous ‘travelling salesman problem’ (also known as ‘the lazy waiter’!);
  • Simulations of iterated Prisoner’s Dilemma and game theory
  • The mathematics of complex networks such as the web or Facebook
  • Applications of statistics to the Premier League, police complaints data and climate change

Compulsory

  • Fundamentals of Mathematics

    Aims to manipulate mathematical expressions accurately, as well as recall and use mathematical formulae in areas of interest for Year 1. To develop skills in handling summation notation. To introduce students to fundamental results in mathematics. To develop an understanding of the need for rigour in definitions and proofs. To introduce the language of formal mathematics, in particular sets and functions.

  • Calculus 1
    This module aims to familiarise students with the basic results, techniques and elementary functions of differential and integral calculus, to introduce students to rigorous definitions, arguments and proofs through many simple examples, to develop students’ manipulative skills in performing operations in differential calculus through work on many simple examples, and to illustrate the solution techniques of first order differential equations.
  • Calculus 2

    Aims to further develop skills in differential and integral calculus and associated applications. To further develop students’ manipulative skills in performing operations in differential calculus through work on examples, including solution techniques of ordinary differential equations.

  • Introductory Programming

    This module aims to provide a basic level of programming competence.  

  • Linear Algebra
    This module aims to enable students to understand and become proficient in basic linear algebra and the algebra of complex numbers, to determine the eigenvalues and eigenvectors of matrices and understand their role in the theory of similar matrices and diagonalization, and to see and practice applications of linear algebra.
  • Programming Applications

    This module aims to provide opportunities for students to apply fundamental programming concepts as a solution to non-trivial problems.  

Compulsory

  • Fundamentals of Alogrithms

    This module aims to develop knowledge and comprehension of various valuable data structures and algorithms, to stimulate critical thinking and enhance skills in evaluating the trade-offs involved in selecting the most suitable algorithms for specific purposes. 

  • Algorithms and their Applications

    This module aims to develop an understanding of a set of useful data abstractions and algorithms, to stimulate students' critical thinking and develop their ability to choose appropriate algorithms in solving practical problems and implementing them in software. 

  • Calculus 3

    Aims to develop ideas and methods of multivariable calculus, including Taylor series, extrema, the use of Lagrange multipliers, and the integration of functions of several variables. To understand the extension from single variable to several variables of basic concepts such as continuity and differentiability.

  • Software Development and Management

    The module aims to develop the knowledge and skills necessary for the design and implementation of software systems using recognised methodology, tools and technologies.  The module provides an introduction to software engineering and follows a development process from requirements and design through to implementation, creating a number of software artefacts. 

  • Discrete Mathematics

    Graphs serve as a background for many important problems in real world applications. This gives an understanding of this area of discrete mathematics, and develops a knowledge of graph theory applications. Also, to introduce operational research optimisation modelling and problem solving and, in particular, linear programming (LP) problems. To introduce algorithms for numerical optimisation and the modelling of random events.

Compulsory

  • Artificial Intelligence

    This optional module aims to develop understanding of the basic principles and techniques for the computer-based simulation and modelling of intelligent behaviour.

  • Final Year Project
    This module aims to stimulate independent learning and critical thinking by the student, both as a means for studying their chosen topic and for approaching other real-life problems, to enable the student to plan and execute a major piece of work with limited input from a more experienced worker, and to give the student experience in the written communication of complex ideas and concepts and the presentation of a substantial piece of work.
  • Software Engineering

    This optional module aims to provide a grounding in topics that directly influence the quality of software, an understanding of key artefacts that inform software quality from a process and product perspective (in particular, the use of and application of software metrics), and to articulate the state-of-the-art in terms of topics such as software patterns, service-oriented engineering and security issues. 

Optional

  • Encryption and Data Compression
    This module aims to familiarise students with techniques widely used in data encryption and compression, and to study mathematical and algorithmic issues and their implications for encryption and compression in practice.
  • Numerical Methods for Differential Equations
    This module aims to introduce numerical methods used to solve problems in financial mathematics, in particular option pricing, and implement them. Most examples treated will be taken from finance, but the module will be suitable for students mostly interested in advanced numerical methods, in particular finite differences algorithms used to approximate solutions of PDEs. The Matlab implementations of the algorithms will be an important part of the module.
  • Ordinary and Partial Differential Equations
    This module aims to introduce students to the mathematics of differential equations; techniques of analysing such equations, and methods of solving them, exactly or approximately.
  • Stochastic Models
    This module aims to introduce students to the concept of a stochastic process, so that they may develop an understanding of the theory underlying some of the standard models and acquire knowledge of methods of applying these models to solve problems. Students will further develop their general ability to think abstractly, to generalise, to formulate and structure stochastic problems, and to apply their knowledge of analytical and numerical mathematical techniques to solving a variety of problems in stochastic modelling.
  • Decision Making in the Face of Risk
  • Deep Learning

    Within this module, an in-depth introduction will be provided to the area of learning using deep neural networks. A wide variety of the architectures of deep neural networks and their learning methods will be covered, including convolutional networks, recurrent networks, generative models and deep reinforcement learning etc. The main focus of the module is to develop students’ skill in analysing of problem requirements, applying appropriate deep learning methods to real-world problems, and evaluating the effectiveness of the adopted approach.

  • Practical Machine Learning
  • Experimental Design and Regression
    The aim of this module is to provide an understanding of the principles of the statistical design of experiments through the study of particular design, of sampling theory for finite populations, and the concepts of survey design.

This course can be studied undefined undefined, starting in undefined.

This course has a placement option. Find out more about work placements available.


Please note that all modules are subject to change.

Careers and your future

Career prospects for mathematics and computer science are excellent. As nearly all businesses today rely on computers, you’ll find that there are opportunities across all of the sectors in large organisations, the public or charity sector or in SMEs. Maybe you want to pursue a career that specifically uses your mathematical, statistical or computing skills or choose a more general career such as management or consultancy. Either way you’ll possess key skills that are highly sought after by business – in fact any industry that uses modelling, simulation, cryptography, forecasting, statistics, risk analysis and probability.

Our combination of work experience and up-to-date teaching means that you will be well-equipped to follow the career you want after graduation.

These are some of the areas where a maths degree is valued highly:

  • Finance: banking, accountancy, actuarial, tax, underwriter, pensions, insurance
  • Medicine: medical statistics, medical and epidemiological research, pharmaceutical research
  • Design: engineering design, computer games
  • Science: biotechnology, meteorology, oceanography, pure and applied research and development
  • Civil Service: scientists (‘Fast Stream’, DSTL, DESG), GCHQ, security service, statisticians
  • Business: logistics, financial analysis, marketing, market research, sales oil industry, management consultancy, operational research
  • IT: Systems analysis, research
  • Engineering: aerospace, building design, transport planning, telecommunications, surveying.

UK entry requirements

2024/25 entry

  • GCE A-level ABB-BBC.
  • BTEC Level 3 Extended Diploma DMM plus A-level Mathematics or Further Mathematics at Grade B.
  • BTEC Level 3 Diploma DM with an A-level at grade B in Mathematics or Further Mathematics.
  • BTEC Level 3 Subsidiary Diploma D with A-level Mathematics.
  • International Baccalaureate Diploma 29 points including 5 in Higher Level Mathematics.
  • Obtain a minimum of 112 UCAS tariff points in the Access to HE Diploma in Computing, Computer Science, Information Technology, ICT or Engineering with 45 credits at Level 3 and grade B in A level Mathematics or Further Mathematics.
  • T levels : Merit overall and grade B in A level Maths.

For Brunel Foundation of Mathematics and Computing with Integrated Foundation Year progression requirements, see the course page.

Five GCSEs at grade C or grade 4 and above are also required, to include Maths and English Language.

Brunel University London is committed to raising the aspirations of our applicants and students. We will fully review your UCAS application and, where we’re able to offer a place, this will be personalised to you based on your application and education journey.

Please check our Admissions pages for more information on other factors we use to assess applicants as well as our full GCSE requirements and accepted equivalencies in place of GCSEs.

EU and International entry requirements

English language requirements

  • IELTS: 6 (min 5.5 in all areas)
  • Pearson: 59 (59 in all sub scores)
  • BrunELT: 58% (min 55% in all areas)
  • TOEFL: 77 (min R18, L17, S20, W17) 

You can find out more about the qualifications we accept on our English Language Requirements page.

Should you wish to take a pre-sessional English course to improve your English prior to starting your degree course, you must sit the test at an approved SELT provider for the same reason. We offer our own BrunELT English test and have pre-sessional English language courses for students who do not meet requirements or who wish to improve their English. You can find out more information on English courses and test options through our Brunel Language Centre.

Please check our Admissions pages for more information on other factors we use to assess applicants. This information is for guidance only and each application is assessed on a case-by-case basis. Entry requirements are subject to review, and may change.

Fees and funding

2024/25 entry

UK

£9,250 full-time

£1,385 placement year

International

£21,260 full-time

£1,385 placement year

Fees quoted are per year and may be subject to an annual increase. Home undergraduate student fees are regulated and are currently capped at £9,250 per year; any changes will be subject to changes in government policy. International fees will increase annually, by no more than 5% or RPI (Retail Price Index), whichever is the greater.

More information on any additional course-related costs.

See our fees and funding page for full details of undergraduate scholarships available to Brunel applicants.

Please refer to the scholarships pages to view discounts available to eligible EU undergraduate applicants.

Scholarships and bursaries

Teaching and learning

Lectures will primarily be delivered in-person on-campus, though some may be delivered online either as pre-recorded or live sessions. The expectation is that you will attend all timetabled on-campus lectures, and that online lectures will be viewed by you in advance of related on-campus activities.

Tutorials & discussion-based sessions will primarily be delivered in-person on campus, though some may be delivered online in order to supplement on-campus learning. You will attend all timetabled on-campus or online tutorials.

Computing Labs will primarily be delivered in-person on campus, though some may be delivered online in order to supplement on-campus learning. The expectation is that you will attend all timetabled on-campus or online computing labs and be provided with access to the specialised software required.

Support/resources: Learning materials for every module will be made available online, through the University’s Virtual Learning Environment.

Assessments will be varied, and may include: CAA (computer aided assessment) tests, written coursework assessments (including software tasks), presentations (in-person or video presentations) and written examinations. You will be expected to attend assessments in-person on campus.

 

Access to a laptop or desktop PC is required for joining online activities, completing coursework and digital exams, and a minimum specification can be found here.

We have computers available across campus for your use and laptop loan schemes to support you through your studies. You can find out more here.

Mathematics at Brunel has an active and dynamic research centre and many of our lecturers are widely published and highly recognised in their fields. Their work is frequently supported by external grants and contracts with leading industry and government establishments. Lecturers are consequently at the frontiers of the subject and in active contact with modern users of mathematics. This means that you can be assured that our academics are teaching you a truly up-to-date degree and you’ll benefit from a wide range of expertise across the different areas of mathematics.

Your academics are always here to help and offer support. There are maths and numeracy workshops run throughout the year where you can seek support in linear algebra, complex calculus, LaTeX, MATLAB and more. You’ll also benefit from the extra support offered to you at our Maths Café. Here you can bring along any maths-related questions and receive one-to-one help in an informal setting.

Should you need any non-academic support during your time at Brunel, the Student Support and Welfare Team are here to help.

Assessment and feedback

The ‘exams to coursework’ ratio is around 50:50 in Level 1, increasing to 70:30 in Level 3.
We base your final degree class on your performance at Levels 2 and 3. Level 3 carries twice the weight of Level 2.