MSc Mathematics and Data Science

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The MSc combines Mathematics with technology from Big Data and analytics, giving you a practical application in financial, business and medical systems, as well as the tools for studying data networks.

Key facts

Award Masters / MSc, Postgraduate Diploma, Postgraduate Certificate
Start date September 2021, January 2022
Duration MSc full-time: 12 months, MSc part-time: 24 months
Mode of study Part-time, Full-time, Campus based, Stand-alone modules

Changes at Stirling

Find out about important changes including how you'll be taught, start dates and how we're making campus safer.

Overview

The field of Data Science has seen rapid growth in recent years, with vast amounts of data now being generated by major companies and service providers.

At the same time, it’s recognised that there’s a shortage of qualified analysts, both in the UK and globally, to make the most of this data. Crucially, there’s now a shortage of mathematics graduates with the data analysis skills needed to meet the demands of industry.

Yet, there is a recognised shortage of qualified analysts, both in the UK and globally, to make the most of this data. 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.

The COVID-19 pandemic has shown the importance of combining Data Science and Mathematics, with governments around the world being guided by predictions from mathematical models. Our MSc is one of the first courses to link these two key areas, making it uniquely positioned to help you meet this demand.

The course will provide you with a strong foundation in the mathematical analysis of data-driven systems and help you develop your computing skills, including Artificial Intelligence and Machine Learning, to apply the techniques you learn on a large scale. You’ll learn the techniques used to approach data using computational analysis and understand the mathematics underpinning these techniques. The key outcome of this course is to ensure you are confident in your skills before you contunue your career.

Stirling is a member of The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. It facilitates industry involvement and collaboration, and provides funding and resources for students.

Top reasons to study with us

This is one of the first courses to link the two key areas of mathematics and data science

96% of our postgraduate leavers are in employment or further study within six months of graduating (Destinations of Leavers from Higher Education survey 2016/17)

You'll learn from a mix of lectures, practical labs and carrying out a dissertation project.

Course objectives

The aim of the course is to teach you the techniques for approaching data sets using computational analysis, and to help you understand the mathematics underpinning these techniques.

On successful completion of the MSc Mathematics and Data Science, you'll be able to:

analyse and solve real-world problems using different mathematical and computational approaches
expand mathematical methods to approach more complex problems
be competant in industry-relevent 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

Work placements

The course features a long summer project, generally in partnership with a company or technology provider.

Flexible learning

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.

Research overview

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.

90% of our research is 'Internationally Excellent' with top 5% judged as 'World-leading' (Research Excellence Framework (REF) 2014)

Entry requirements

Please select your country of residence:

Academic 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.

Applicants with a mathematics degree (including a joint mathematics degree) will be accepted.

Other routes of entry

If you don’t currently meet the academic requirements for this course, INTO University of Stirling offers a variety of preparation programmes that can earn you the qualifications and skills you need for direct entry.

Explore INTO Stirling programmes to see the pathway and pre-masters routes available for this course and others at the University of Stirling.

English language requirements

Due to disruption in English Language testing caused by COVID-19, we are accepting alternative English Language tests (including online English Language Tests).

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:

IELTS Indicator 6.0 with a minimum of 5.5 in each sub-skill
Cambridge C1 Advanced (CAE) 169 overall with a minimum of 162 in each sub-skill
Cambridge C2 Proficiency (CPE) 180 overall with a minimum of 162 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
IBT TOEFL Special Home Edition Test 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing
Trinity ISE II Pass overall with a Pass in each sub-skill, ISE III Pass overall and in all sub-skills, ISE IV Pass overall and in all sub-skills
Aptis (4 skills) CEFR B2 overall and B2 in all sub-skills
Duolingo 95 overall with a minimum of 90 in all sub-skills
LanguageCert International ESOL B2 Communicator - Pass with minimum 33 in each sub-skill

Last updated: 1 February 2021

For more information on ways that you can meet our English language requirements, including options to waive the requirement, please read our information on English language requirements.

Pre-sessional English language courses

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 lectures and practical labs during the Autumn and Spring semesters.

In the summer semester, you will carry out a research dissertation project. The project may 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, National Health Service (NHS) and Scottish Enterprise.

The course covers:

statistical analysis techniques for small and large datasets
data analysis and modelling using R, Matlab and Python
building and analysis of mathematical models of real-life systems
mathematical analysis of data networks, e.g. social media networks
analytical optimisation and computer-based search algorithms, including Artificial Intelligence
data analytics and machine learning
relational and non-relational databases*
cluster computing*

*Optional modules for students starting in October.

Modules

The modules listed below are those currently intended for delivery in the current academic intake of this course. These may be subject to change in future years as the University regularly revises and refreshes the curriculum of our taught programmes.

Course Details

Teaching

You'll learn from lectures and practical labs.

Assessment

You’ll be assessed by a variety of assessment strategies, including written assignments, exams and individual projects.

Course director

Dr Andrew Hoyle

+44 (0)1786 467467

andrew.hoyle@stir.ac.uk

Fees and funding

Fees and costs

Select fee status:

	2020/21	2021/22
Students from the UK	£8,500	£9,350
Overseas (non-EU) students	£20,750	£20,845
EU students	£8,500	£20,845

Fees shown are for a full-time, one-year Masters course.

If you need to extend your period of study or repeat study, you will 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.

Tuition fee loans

Scottish students may be eligible to apply to the Students Award Agency for Scotland (SAAS) for loans of up to £10,000 to cover tuition fees and associated living costs. EU students commencing their studies in academic year 2020/21 can also apply for tuition fee support, but may not be eligible to receive funding for living costs.

English students can apply for a loan of up to £11,222 per year as part of the Postgraduate Masters Loan Scheme.

Welsh students can apply for financial support of up to £17,489 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 £5,500 from Student Finance NI.

For EU students starting studies in the academic year 2021/22, we will offer a fee discount of 40%. This is subject to eligibility criteria.

Fees shown are for a full-time, one-year Masters course.

If you need to extend your period of study, you will 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.

We offer a range of funding options for overseas students.

Fees shown are for a full-time, one-year Masters course.

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.

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.

Scholarships and 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.

Cost of living

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.

EU and overseas 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.

Find out about the cost of living for students at Stirling

Payment options

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

Graduates from a data science course find employment as:

R&D data scientist
digital analytics engineer
data engineer
data scientist
machine learning engineer
machine learning data scientist
data solution architect
machine learning developer
data scientist in a research field such as genomic, cognitive, clinical and healthcare

96% of our postgraduate leavers are in employment or further study within six months of graduating (Destinations of Leavers from Higher Education survey 2016/17)

Our career services is 1st in Scotland, top 5 in the UK and top 15 in the world (UK International Student Barometer (ISB) Benchmark and Global ISB Benchmark 2018)

Employability skills

Our new MSc Mathematics and Data Science was designed with employability firmly in mind. This has shaped the modules and how the course is assessed.

Here at Stirling, you'll be offered workshops on CV writing, interview technique and how to secure that dream job. Our relationship with employers and recruiters is strong and they regularly attend events at the University with the intention of recruiting staff.

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MSc Mathematics and Data Science

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MSc Mathematics and Data Science

Key facts

Changes at Stirling

Overview

Top reasons to study with us

Course objectives

Work placements

Flexible learning

Research overview

Entry requirements

Academic requirements

Other routes of entry

English language requirements

Pre-sessional English language courses

Course details

Modules

Course Details

Teaching

Assessment

Course director

Fees and funding

Fees and costs

Additional costs

Scholarships and funding

Cost of living

Payment options

After you graduate

Employability skills

What next?

Which course would you like to apply for?

MSc Mathematics and Data Science

Key facts

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Which course would you like to apply for?