Why choose this course
Data science has become increasingly important in many areas over the past two decades. These include banking, finance, insurance, weather forecasting, image analysis, genomics, advertising, transport and elections. The discipline is even used in policing and crime prevention. Data sets can unravel all kinds of facts, trends, anomalies and patterns – but only with the right technical skills!
Mathematical data science is an interdisciplinary area of applied mathematics. It combines methods and techniques from a broad range of pure and applied subjects within maths to develop approaches that enables us to investigate large data sets. These techniques include:
- Data representation
- Information theory
- Machine learning optimisation
- Numerical methods
- Statistical analysis
The objective of our MSc in Mathematical Data Science is to guide you through a range of sophisticated mathematical ideas underlying modern data science. You’ll understand the mechanisms for modelling data-producing dynamical phenomena. We’ll also equip you with both the theoretical and the computational skills to analyse and extract information from large data sets.
What you will study
Our MSc benefits from the wide range of research being carried out in the Department of Mathematics. The taught courses and dissertation topics available to you are closely aligned with some of the activities of the Department’s research areas. These include:
- Data science and dynamics
- Mathematics of life and social sciences
- Nonlinear waves and geometric fluid dynamics.
During the first two semesters, you'll select a range of taught modules. These will be followed by an extended research project conducted over the summer under the supervision of a member of the Department. In some cases, this will be in conjunction with a second external supervisor, culminating in the writing of an MSc dissertation.
The modules you’ll study are listed below:
- Data Science for Dynamical Systems
- Data Science Principles and Practices
- Mathematics of Data Science
- Topics in Applied Statistics.
- Bayesian Inference for Data Science
- Dynamic Asset Pricing Theory
- Image Processing and Deep Learning
- Machine Learning and Data Mining
- Mathematical Modelling of Markov Chain Monte Carlo
- Statistical Methods with Financial Applications.
Please note: this information is subject to change.
Our Department of Mathematics has strong links to the National Physical Laboratory, the Meteorological Office and other external partners collaborating on a range of research topics in or around data science. We also host a research group in Data Science and Dynamics, focusing on the study of dynamical systems that generate large data sets.
Careers and graduate prospects
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University. Our graduates have lifetime access to Surrey Pathfinder, our online portal for appointment and events bookings, jobs, placements and interactive development tools.
The University of Surrey has an excellent record for graduate employability. We were named University of the Year for Graduate Employment in The Times/Sunday Times Good University Guide for 2022. We also run an award-winning Professional Training Placements scheme, which gives students industry experience and prepares them for roles in various sectors.
Mathematics is of paramount importance to all aspects of science, technology and modern finance. The logical insights, analytical skills and intellectual discipline gained from mathematical studies are highly sought after in all of these areas, as well as in a broad range of other disciplines such as law, business, management, ecommerce and the creative arts.
As well as being designed to allow candidates to meet the needs of future employers, our MSc provides a solid foundation from which to pursue further research in mathematics, or one of the many other disciplines to which mathematical ideas and techniques are applied. In particular, as a data scientist or a machine learning engineer, you’ll be well positioned for a range of specialist roles.
Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability, student demand and/or class size caps.
Important: In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases, the content) of its programmes. Find further information on the general principles of hybrid learning.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2022/23 This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
The University operates a credit framework for all taught programmes based on a 15-credit tariff. Modules can be either 15, 30, 45, 75 and 120 credits, and additionally for some masters dissertations, 90 credits.
The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:
Please note: this course is subject to validation, therefore no modules have been confirmed at this moment in time. These modules will appear once the course has been validated.
Course timetables are normally available one month before the start of the semester. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day of the week (Monday - Friday). Wednesday afternoons are normally reserved for sports and cultural activities. Part-time classes are normally scheduled on one or two days per week, details of which can be obtained from the Academic Hive. View our Timetabling Policy (PDF).
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
A minimum of a 2:1 in a relevant UK honours degree in Mathematics or related areas (such as Physics or certain areas of Engineering and Computer Science).
International entry requirements by country
Do I meet the requirements for this course?
We require you to submit a full application so that we can formally assess whether you meet the criteria published. Unfortunately, we are unable to provide an outcome based on an enquiry (via email, webform enquiry, phone or live chat).
English language requirements
IELTS Academic: 6.5 overall including 6.0 in Writing and 5.5 in each other component.
View the other English language qualifications that we accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.
The University of Surrey recognises that many students enter their higher education course with valuable knowledge and skills developed through a range of professional, vocational and community contexts. If this applies to you, a process called recognition of prior learning (RPL) may allow you to enter your course at a point appropriate to your previous learning and experience, or to join the start of a course without the formal entry requirements. This means that you may be exempt from certain elements of study in the course for which you have applied and be awarded credit based on your previous qualifications/experience. There are restrictions on RPL for some courses and fees may be payable for certain claims.
Please see the code of practice for recognition of prior learning and prior credit: taught programmes (PDF) for further information. Please email Admissions (firstname.lastname@example.org) with any queries.
Start date: October 2022
Full-time - 1 year
- These fees apply to students commencing study in the academic year 2022-23 only. Fees for new starters are reviewed annually
- If you are on a two-year full-time Euromasters or MFA programme, or a two-year or three-year part-time masters programme (excluding modular/self-paced/distance learning), the annual fee is payable in Year 1 and Year 2 of the programme
- Annual fees will increase by 4% for each subsequent year of study, rounded up to the nearest £100, subject to any overriding applicable legislative requirements.
You may be able to borrow money to help pay your tuition fees and support you with your living costs. Find out more about postgraduate student finance.
Scholarships and bursaries
We're committed to making sure that we offer support for students who might need it.
Vice-Chancellor's Excellence Scholarship
Terms and conditions
When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our policies and regulations, and our terms and conditions. These terms and conditions are provided in two stages: first when we make an offer and second when students who have accepted their offers register to study at the University. View an example of our offer terms and conditions and our generic registration terms and conditions (PDF) as a guide as to what to expect.
Please note: our offer terms and conditions will generally be available in the September of the calendar year prior to the year in which you begin your studies. Our registration terms and conditions will vary to take into account specifics of your course and changes for the specific academic year.
This online prospectus has been prepared and published in advance of the academic year to which it applies. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read more.
In light of the COVID-19 pandemic, the University has had to change the delivery (and in some cases, the content) of its programmes, together with certain University services and facilities for the academic year 2022/23. These changes include the implementation of a hybrid teaching approach during 2022/23.
Subject to validation
This programme is subject to approval. This means that it has received initial agreement from the University and is currently undergoing a detailed final approval exercise, through the University’s quality assurance processes. These processes are a requirement for all Higher Education Institutions within the UK, to ensure that programmes are of the highest standard. Occasionally there may be instances where the University may delay or not approve the introduction of the programme.