Overview
The field of data science is seeing rapid growth, with vast amounts of data now being generated by major companies and service providers.
Yet, there is a recognised shortage of qualified analysts, both in the UK and globally, to make the most of this data and to meet the demands of industry. In particular, the demand is for graduates who can both manage the data (the computing skills), and analyse the data to extract patterns, build models and make predictions (the mathematics skills). It is only with these analytical skills can the full value of data be extracted.
Launched in 2018, our Masters is one of the
The course will provide you with a strong foundation in mathematical modelling and the analysis of data-driven systems and help you develop your computing skills, from programming Python and R, to advanced techniques including Artificial Intelligence and Machine Learning, to applying the techniques you learn on a large scale. You will learn the techniques used to approach data and build models using computational analysis and understand the mathematics underpinning these techniques.
Our graduates have gone on to work in financial institutions, major energy firms, sport and fitness, start-ups, software providers, NHS and pharmaceutical organisations, environmental agencies, and the Scottish Government. Many have undertaken PhDs in the UK and across the world.
Stirling is associated with The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. The Data Lab:
- supports our students with funding, networking and routes into employment;
- facilitates industry involvement and collaboration;
- provides funding and resources for students.
"Shape your world with Stirling. I've come from the consulting industry to enhance my data science skill; and the student friendly faculty and concrete curriculum at The University of Stirling provided the right environment for me to do so."
Nuzhat Nishi
The aim of the course is to teach you the techniques for approaching data sets using computational analysis; to help you understand the mathematics underpinning these techniques; and to be confident in applying these techniques to real-life scenarios.
On successful completion of the MSc Mathematics and Data Science, you will be able to:
- analyse and solve real-world problems using different mathematical and computational approaches;
- build, parameterise and analyse mathematical models to real-life problems;
- expand mathematical methods to approach more complex problems;
- be competent in industry-relevant programming languages, including R, Python and Matlab;
- demonstrate skills in data analytics, Machine Learning and Artificial Intelligence (AI);
- analyse small and large-scale data sets using mathematical and computational approaches;
- be confident in your own research and data science skills through real-life based projects.
The course features a substantial summer project. Where available, these can be done in partnership with a company or technology provider.
If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.
Our team of academics in the department of Computing Science and Mathematics investigate novel and effective approaches to dynamic and uncertain real-world problems in complex systems and environments. They explore the interdisciplinary connections between computer science, mathematics, life sciences, social sciences and management.
We work collaboratively with a number of organisations, including The Data Lab (Scotland’s Data Science Innovation Centre, which supports students with funding, networking and routes to employment) and the Scottish Informatics and Computing Science Alliance (SICSA), to ensure our students have the best platform to succeed.
Entry requirements
A minimum of a second-class Honours degree, or equivalent, in a numerate subject, e.g. mathematics, physics, engineering, economics; along with some evidence of a mathematical background, such as having taken and passed mathematics modules in at least some of calculus, algebra, statistics and numerical analysis.
Other routes of entry
If you don't currently meet our academic requirements, INTO University of Stirling offers a variety of preparation programmes that can earn you the qualifications and skills you need to progress onto some of our courses. Explore INTO University of Stirling to see the pathway and pre-masters routes available.
International entry requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Academic or UKVI 6.0 with a minimum of 5.5 in each sub-skill.
- Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill.
- IBT TOEFL 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing.
See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.
If you need to improve your English language skills before you enter this course, our partner INTO University of Stirling offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.
Find out more about our pre-sessional English language courses.
Course details
The MSc Mathematics and Data Science is taught by the Division of Computing Science and Mathematics in the Faculty of Natural Sciences. You'll learn from lecturers whose research expertise is in mathematical modelling, data science and AI. During the Autumn and Spring semesters, this course covers:
- statistical analysis of large datasets and data in network form, e.g. social media networks (MATPMDB)
- basic and advanced programming using R, Matlab and Python (multiple modules)
- building and analysing mathematical models of real-life systems (MATPMD3)
- probability, stochastic optimisation and Artificial Intelligence (MATPMD4)
- data analytics and machine learning* (ITNPBD6)
- relational and non-relational databases* (ITNPBD3)
- cluster computing* (ITNPBD7)
*Optional modules.
In the summer semester, you'll carry out a research dissertation project on an application of your choice. The project may be part of a cutting-edge research project at the University, be of your own design, or as part of a placement or consultancy project for a company, where possible. Past placements include Loch Lomond and Trossachs National Park, NHS, Natwest Bank and Filament – a data science start-up. (Many of these are arranged through the Data Lab for scholarship holders.)
For the course that starts in January, the duration of the course is 21 months. For example, students starting in January 2024 will graduate in November 2025.
Modules
The module information below provides an example of the types of course module you may study. The details listed are for the academic year that starts in September 2024. Modules and start dates are regularly reviewed and may be subject to change in future years.
Course Details
Core teaching will take the form of lectures and recorded videos from the lecturer, allowing you to study at your own pace. In addition, you will have small group discussion groups and practical sessions. These allow you to ask questions, learn from peers and practice the material covered in the core teaching material.
During the summer, you will carry out a research project of your choice. This project is usually based around a real-life problem and requires the analysis of a data set or the building of a mathematical model. This provides a great opportunity to showcase the skills learnt during the course and demonstrate to employers you can use the skills developed.
We have a programme of invited speakers from industry giving you the opportunity to ask questions of people who are doing data science every day. Recent participants include MongoDB, SkyScanner and HSBC.
Assessment is primarily through coursework and projects. These projects often involve analysing real-life data or applying the methods from the module to a specific application. There are also presentations, group assignments and research projects to further develop your skills.
Fees and funding
University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our Stirling Alumni Scholarship.
Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our Postgraduate Merit Scholarship.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, the total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Eligible students could receive a scholarship worth between £4,000-£7,000. See our range of generous scholarships for international postgraduate students.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, the total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Postgraduate tuition fee loans
This course is eligible for a postgraduate tuition fee loan from one of the UK’s governments. See the Scholarships and funding section, below, for more details.
Additional costs
There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees.
Funding
If you have the talent, ability and drive to study with us, we want to make sure you make the most of the opportunity – regardless of your financial circumstances.
Learn more about available funding opportunities or use our scholarship finder to explore our range of scholarships.
Postgraduate tuition fee loans
Scottish students may be eligible to apply to the Students Award Agency for Scotland (SAAS) for loans of up to £11,500 to cover tuition fees and associated living costs.
English students can apply for a loan of up to £12,167 each year as part of the Postgraduate Masters Loan Scheme.
Welsh students can apply for financial support of up to £18,770 as a combination of grant and loan from Student Finance Wales.
Northern Irish students can apply for a postgraduate tuition fee loan of up to £6,500 from Student Finance NI.
International students may be able to gain additional funding from loan providers.
If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.
International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.
We aim to be as flexible as possible, and offer a wide range of payment methods - including the option to pay fees by instalments. Learn more about how to pay
After you graduate
As opposed to focussing on a single application or field, this course was designed to give you the core skills needed to go into various sectors.
Our graduates have gone on to work in financial institutions, energy firms, sport and fitness, start-ups, NHS and pharma, environmental agencies, government agencies, as well as undertaking PhDs in the UK and across the world.
“I bridged my knowledge gap on mathematics, while learning data science, and I am now much more assured when working with numbers and data in general. The assignments and tutorials were effective in teaching the major programming languages – Python and R – and I am confident now in applying them to real-world projects.”
George Vekic
Our MSc Mathematics and Data Science was designed with employability firmly in mind. This has shaped the modules and how the course is assessed.
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