Our Mathematics (including foundation year) BSc (Hons) is a four-year course with a built-in foundation year (Year 0), an ideal choice if you don’t have the necessary qualifications to study a standard degree. This foundation course is accredited by the Institute of Mathematics and its Applications (IMA). This course will provide you with a range of practical skills in mathematics as well as work experience which will be invaluable to you when embarking on a career related to mathematics.
Our Mathematics (including foundation year) BSc (Hons) degree begins with a preparatory year designed to build your confidence and academic capabilities while helping you gain skills in several areas. This preparatory year will help you attain all the base knowledge you’ll need to succeed during the rest of your course.
The foundation year on this course is shared with other foundation year degrees. In this preparatory year you’ll learn a variety of skills across different subjects, including cyber security, computer networks, mathematics and programming, helping you to build an understanding of the fundamentals of mathematics.
If you find yourself more interested in a different area of mathematics or computing following your foundation year there is the option to specialise.
London Met has an advanced Cisco lab, IT security lab, electronics and microprocessor labs to facilitate your studies. The University also has connections with major companies such as Cisco, Microsoft, Adobe, Oracle and IMB to ensure you gain all the industry experience and skills to succeed in your career.
Following your foundation year, you’ll study the same course content and get the same choice of modules as those who study our Mathematics BSc (Hons) degree.
You'll graduate with a full undergraduate degree with the same title and award as those who studied the traditional three-year course.
You can get a taste for life at our School of Computing and Digital Media by taking a look at our showcase of recent student work.
Your assessments will include:
This course is accredited by the Institute of Mathematics and its Applications (IMA).
We are planning to return to our usual ways of teaching this autumn including on-campus activities for your course. However, it's still unclear what the government requirements on social distancing and other restrictions might be, so please keep an eye on our Covid-19 pages for further updates as we get closer to the start of the autumn term.
In addition to the University's standard entry requirements, you should have:
Applicants who meet the UCAS points criteria but who obtained a grade D/grade 3 in English and/or Maths at GCSE may be offered a University test in these areas.
Any university-level qualifications or relevant experience you gain prior to starting university could count towards your course at London Met. Find out more about applying for Accreditation of Prior Learning (APL).
To study a degree at London Met, you must be able to demonstrate proficiency in the English language. If you require a Student visa you may need to provide the results of a Secure English Language Test (SELT) such as Academic IELTS. For more information about English qualifications please see our English language requirements.
If you need (or wish) to improve your English before starting your degree, the University offers a Pre-sessional Academic English course to help you build your confidence and reach the level of English you require.
The modules listed below are for the academic year 2021/22 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.
Year 0 modules include:
On this module students will learn the fundamental knowledge concerning computer security, basic cyber threats and the corresponding detection and defence techniques. Core security concepts, terminology, technologies and professional cyber security skills will be introduced via case studies and laboratory experiments.
This module aims to introduce basic hardware and software elements relevant to robotics and internet of things (IoT) at foundation level (level 3). In particular, the module is designed to provide students with an introductory overview and practical experience in design and development of a simple system involving elements of robotics and IoT.
The module covers the necessary principles and theory through formal lectures/seminars followed by comprehensive laboratory practice involving workshop-based exercises and a case study.
This module introduces students to a range of mathematical techniques involving algebraic properties and graphs of the algebraic, logarithm, exponential and trigonometric functions. Furthermore the module introduces mathematical techniques of differentiation and integration of simple functions.
The module introduces students to theoretical concepts underpinning computer software design; and to programming using a high-level language concentrating on sequence, selection, iteration (loops) and list processing. It is assessed by three individual online tests (20%, 20%, and 30% weighting) and a group programming assignment (30% weighting).
It aims to enable the student to use a programming language in a familiar and confident way in a variety of practical situations, and to use an integrated programming development environment competently.
It also enables the student to design and write simple programs, individually and in groups, using the programming language constructs described in the syllabus below; and to develop techniques to ensure software quality and robustness, and to produce a reflective report.
Year 1 modules include:
The module covers basic mathematical techniques of differential and integral calculus and of linear algebra that will be of later use throughout Mathematics and related degree courses. The module builds on and extends concepts learned in A-Level Mathematics. The contents covered and the skills developed are fundamental to the development of mathematical competence. Calculus and linear algebra form an important foundation for further studies in Mathematics, Finance, Statistics and Engineering.
This module develops the mathematical and statistical tools that are used in the mathematics of finance. It also introduces methods of analysing data using appropriate statistical software.
This module introduces the basic terminologies used in finance and develops the mathematical techniques to solve problems in the area of finance. Descriptive statistics and statistical techniques that are useful to present, analyse and make inferences about data are also introduced. A selection of suitable software (e.g. Excel, R, SPSS) will enable students to analyse data in order to make informed decisions.
This module introduces a range of numerical approximation methods for solving a variety of mathematical problems, including iterative methods for solving nonlinear equations and systems of linear equations. This module also introduces a mathematical programming package that is commonly used for solving a variety of problems. The application of these techniques, through the medium of mathematical problems enables the student to become proficient in the use of algebraic software which is used in most mathematical related jobs such as working in industry, financial markets and teaching.
This module develops the skills necessary to support academic study at degree level. It will also develop reflective learning and action planning via the Personal Development Planning (PDP) process. The first term topics will look into history of mathematics , development of modern number system and introduce idea of mathematical proofs. Different proof techniques will be covered using examples from Set Theory and Number Theory.
The topics covered in the second term part of this module is to introduces the main ideas of graph theory and includes a variety of algorithms.
Year 2 modules include:
The module extends the students’ knowledge of the techniques of calculus and introduces the concept of differential equations.
This module aims to give students a thorough understanding of the analytical techniques available to solve first and second order ordinary differential equations.
The topics covered in the first term of this module is to introduce formal inductive and recursive structure on the natural numbers. This structure underlies many aspects of program design and validation, and formal methods. An introduction to combinatorics and the generating functions are designed to enhance the students algorithmic tool set.
The topics covered in the second term part of this module is to introduce students to the abstract algebraic structures of groups, which arise from the ideas of symmetries and of vector and matrix calculus respectively. These two primary examples of algebraic structures have applications across science and engineering, and also provide a firm foundation of necessary basic algebraic notions for the student to further their study mathematical study.
The module extends the students’ knowledge of the techniques of calculus and introduces the concept of multivariable Calculus as well as calculus of vectors.
This module introduces Vector-Valued Functions and extends ideas of calculus of one dimension to Vector-Valued Functions.
Prior knowledge: MA4010 Calculus and Linear Algebra
This module introduces a selected range of Operational Research techniques that are commonly used for solving a variety of small to medium size problems, through the medium of spreadsheet and other suitable software. It also enables the student to investigate real-life problems of business and industrial problems of varied complexity.
This module enables the student to further develop and apply numerical techniques to a range of problems including the solution of ordinary differential equations related to both physical and financial/economic models.
This module enables the student to further develop and apply numerical techniques to a range of problems including the solution of ordinary differential equations related to both physical and financial/economic models.
The aims are:
To enable students to apply approximation techniques to problems of both theoretical and practical importance and understand the cause of and interpret the degree of error involved;
To prepare students with the tools necessary for solving a range of problems in situations suitably described by ordinary differential equations and by difference equations;
To understand modelling with linear and nonlinear dynamical systems and iterative methods of solution;
To enable students to understand and manipulate coded programmes for software packages such as Maple for solving larger problems.
To develop students’ knowledge, confidence and problem solving skills leading to further academic progression and future employability in this area.
The module covers mathematical and statistical modelling techniques that are applied in making decisions in areas of finance. It also enables the student to investigate real-life statistical data.
This module introduces important financial concepts and develops statistical modelling techniques. Statistical regression models are applied to financial data (e.g., credit scoring, default time analysis) and mathematical modelling of stock and option prices is investigated. A selection of suitable software (e.g. Excel, R, SPSS) will enable students to analyse data in order to make informed decisions. The students will develop skills in statistical and mathematical modelling of real data to aid future employability.
Year 3 modules include:
This module serves as a core module for all maths students to do a one-semester project in the broader sense and as an alternative to the Faculty’s 30 credit Project module. The feature of the module is summarised as follows.
1. Students will follow their own interest to pursue an individualised study independently under staff supervision.
2. Students taking this module with the same supervisor may study the same subject but the assessments should be individualised.
3. The allocation of supervisors to students should be done at the end of year two. Students can take this module in either autumn or spring period.
The programme of study is very much individualised and there is a variety of format. The following are just two typical examples: (a) Pursue an investigative study on a particular topic, with an assessment of written report plus viva, and (b) A self-negotiated study in any subject area following a printed textbook or online material, assessed by a coursework consisting of a mixture of solutions to exercise questions, a written report, and a viva (oral presentation). In the later case, there must be an “investigative and independent factor” in the study. Any other innovative format is encouraged.
The module aims to
1. Provide students with an opportunity to pursue an academic area of interest independently, subject to the availability of an appropriate supervisor, where a taught module is not available.
2. Develop students’ ability to search the internet and library for useful information.
3. Enrich students’ experience of self-negotiated study.
4. Improve students’ employability by enhancing their skills through report writing and reflection on independent learning.
This module extends students’ knowledge of linear algebra and calculus, providing greater depth and rigour for these essential topics.
The aim of the first part of the module is to introduce students to the abstract algebraic structures of vector spaces, developing on the material on linear algebra learnt at level 4. This primary example of algebraic structures has applications across science and engineering, and also provides a firm foundation of necessary basic algebraic notions for the student to further their study mathematical study.
The aim of the second part of the module is to develop a rigorous approach to the analysis of functions of a real and a complex variable. Further topics in complex integration are also covered and students are introduced to applications of these topics to improper integration of functions of a real variable.
This module develops a rigorous approach to the whole process of solving problems arising from real life scenarios and the module consists of providing solutions to a number of such problems. For each given problem, the process of dealing with it includes an initial analysis, identification of the main factors involved, establishment of a differential or difference equation as a mathematical model of the problem, analytical and/or numerical analysis to solutions of the equation, making predictions and drawing conclusions to the model, and feedback to solving the problem.
The module aims to
1. Introduce the process of model building from a non-mathematical description of a physical or industrial process or in a business application.
2. Introduce the idea of mathematical modelling as a means of solving real problems.
3. Present powerful tools of differential/difference equations to analyse the models in order to make appropriate predictions.
4. Develop the student's ability to work effectively in-groups.
5. Improve the student's communication skills through report writing and presentation.
Pre-requisite knowledge: MA5011 Further Calculus and MA5052 Differential Equations (studied or Co-requisite)
The module enables students to undertake an appropriate short period of professional activity, related to their course at level 6, with a business or community organisation and to gain credit for their achievements. The activity can be a professional training, a volunteering activity, employment activity, an activity within the School of Computing and Digital Media Virtual Business Environment (VBE), placement or business start-up activity.
For the purpose of this module – the VBE will be also be recognised as ‘the employer’.
It is expected student should work for 150 hours which should be recorded clearly (in a learning log for instance) in the portfolio. The 150 hours can be completed in 25 working days in a FT mode, or spread over a semester in a PT mode.
Students should register with the module leader to be briefed on the module, undergo induction and Work Based Learning planning and to have the Work Based Learning approved, before they take up the opportunity. It is essential that students are made aware that both the “Work Based Learning agreement” and relevant “health and safety checklist” where applicable need to be approved before starting the learning activity.
The module aims to provide students with the opportunity to:
• gain a useful experience of the working environment and the career opportunities available on graduation.
• undertake a work-based project appropriate to their academic level.
• enhance and extend their learning experience by applying and building on their academic skills and abilities by tackling real life problems in the workplace.
• enhance professional and personal development.
The module is an introduction to modern ideas in cryptography. It proves the background to the essential techniques and algorithms of cryptography in widespread use today, as well as the essentials of number theory underlying them.
The module looks at symmetric cipher systems and their use in classical cryptography as well as public key systems developed to support internet commerce and deliver data security for private individuals.
The module is an introduction to modern ideas in error correcting codes. It provides the background to the essential techniques and algorithms in widespread use today, as well as the essentials of number theory and finite field theory underlying them.
Error correcting codes are an important part of the data communications theory and allow a message to be recovered even if errors have been introduced during transmission. The elegant mathematics of finite field theory is introduced to develop multiple error correcting codes with a wide range of communications applications.
The module introduces the students to financial forecasting using modern statistical modelling techniques. Its aim is to prepare the student for work in a quantitative commercial or scientific environment. Students will be developing problem solving skills. For each given problem, the process of dealing with it includes, searching for appropriate data sets, establishing the right statistical/financial techniques to use, fitting appropriate models, critically appraising the models using diagnostic model tools and finally interpreting the models and drawing conclusions.
"Lecturers at London Met are very supportive. They will actually spend hours outside the classroom helping you understand everything. Nino, our course leader, supports everyone and makes personal recommendations so that all students can succeed."
Maria Koukiali, Mathematics BSc (Hons) student, 2021
"I did my work-related learning module and helped in the maths department at a secondary school. That was really helpful as I plan on going on to get my PGCE so I can teach maths."
Vivienne Cleary Spoerri, Mathematics BSc (Hons) student, 2021
"I'm happy with my course and I hope to find a job in finance afterwards. I've always felt very supported by my lecturers. The Mathematics BSc course leader, Nino Folic, supported me through all the three years of the course and was always available when I needed his help. Even as a mature student, I've never felt too old to be in university. I enjoyed the University so much that I didn't want to leave! [So] I started a master's in Data Analytics at London Met."
Antonella Petrocco, Mathematics BSc (Hons) graduate, 2020
"I wanted to go somewhere in London, somewhere quite central, and London Met was the best place for it. All of the subjects and the teachers are quite fun. They prepared me a lot, they help you look for jobs, help you with interview skills. There's a lot of opportunities at London Met. I love London Met, I had a great time — everyone has a good time."
Nathan Walton, Mathematics BSc (Hons) graduate, 2018
"I want to be a maths teacher — I've actually applied to a PGCE [here]. You're going to have a great time, keep yourself involved, you're going to widen your experience. Throughout the past three years every day was a special day, knowing that I'm getting closer to my career and my dream."
Muhammed Hamid Shaikh, Mathematics BSc (Hons) graduate, 2017
A degree in mathematics can open up a wide range of career options. You could take up a role in scientific research, design and development, management services, computing, financial work, statistical work or teaching. You could also go on to do postgraduate study.
This is a four-year degree course with a built-in foundation year (Year 0). It's the perfect route into university if you can't meet the necessary entry requirements or don't have the traditional qualifications required to start a standard undergraduate degree. You'll graduate with a full undergraduate degree with the same title and award as those who studied the traditional three-year course.
Please note, in addition to the tuition fee there may be additional costs for things like equipment, materials, printing, textbooks, trips or professional body fees.
Additionally, there may be other activities that are not formally part of your course and not required to complete your course, but which you may find helpful (for example, optional field trips). The costs of these are additional to your tuition fee and the fees set out above and will be notified when the activity is being arranged.
Discover Uni is an official source of information about university and college courses across the UK. The widget below draws data from the corresponding course on the Discover Uni website, which is compiled from national surveys and data collected from universities and colleges. If a course is taught both full-time and part-time, information for each mode of study will be displayed here.
If you're a UK applicant wanting to study full-time starting in September, you must apply via UCAS unless otherwise specified. If you're an international applicant wanting to study full-time, you can choose to apply via UCAS or directly to the University.
If you're applying for part-time study, you should apply directly to the University. If you require a Student visa, please be aware that you will not be able to study as a part-time student at undergraduate level.
If you're applying for a degree starting in January/February, you can apply directly to the University.
The University and Colleges Admissions Service (UCAS) accepts applications for full-time courses starting in September from one year before the start of the course. Our UCAS institution code is L68.
If you will be applying direct to the University you are advised to apply as early as possible as we will only be able to consider your application if there are places available on the course.To find out when teaching for this degree will begin, as well as welcome week and any induction activities, view our academic term dates.
Please select when you would like to start:
The highly-commended book, 'Flexible Regression and Smoothing,' aims to help readers understand how to learn from data encountered in many fields.
Our careers-focused University placed in the top ten for student satisfaction for Music, Mathematics and Economics.
The School of Computing and Digital Media's Summer Show will be held on 6 - 7 June in the world famous Graduate Centre. Events to celebrate the School will take place from 6 - 14 June.
Art courses ranked second best in London again for student satisfaction, while the School of Computing and Digital Media's Maths course scores 10/10 for ‘Value Added’.