Course summary
Mathematics and data science are closely connected. Data science methodologies are built on mathematical principles. Understanding them is crucial for aspiring data scientists (source: Institute of Data 2023). The demand for graduates in this field is growing rapidly fuelled by advances in technology and the increasing importance of data (Data Science Jobs, 2025). Employers seek individuals with computing skills to manage data and mathematical skills to analyse it. This involves identifying patterns, building models, and making predictions. Our Masters degree in Mathematics and Data Science emphasises the practical application of mathematics for data science. You’ll develop skills that are highly sought after in the data industry. Gain practical maths and data science experience On our Mathematics and Data Science MSc, you get the opportunity to work with academics on commercially relevant research projects. You can also take part in projects with industry or technology providers. Past projects include: Intergen: Data driven forecasting of UK electricity market imbalances Natwest: Building enterprise scale machine learning ops - model monitoring toolkits Scottish National Investment Bank: The decarbonisation of heat in Scotland SportScotland Institute of Sport: Analysis of swimming race data Streamba Ltd: Assessing methods for robust data preparation of heterogeneous sources Eden Court Highlands: Live audience analysis National Records of Scotland: Seasonal adjustment of mortality BBC World Service: Analysis of shifts in political/public opinion using time series analysis and natural language processing tools Learn cutting edge skills which are in demand from employers You'll gain hands on industry standard skills and knowledge from lecturers with research expertise in mathematical modelling, data science and AI. The course covers: statistical analysis of large datasets and data in network form, e.g. social media networks; basic and advanced programming using R, Matlab and Python; building and analysing mathematical models of real-life systems; probability, stochastic optimisation and artificial intelligence; data analytics and machine learning; relational and non-relational databases; cluster computing. Engage with the data science industry This data science and mathematics Masters degree offers a great chance to build your professional network with peers and industry leaders. You’ll benefit from our strong ties with The Data Lab innovation centre who offer networking opportunities. You’ll also engage with industry through guest lectures and local industry career events. Recent speakers include Huawei, Bigspark, Red Star (AI for healthcare), Virtonomy, KBC Group, and Leonardo UK.
Modules
Statistical analysis techniques for small and large datasets; Developing models of real-life systems; Mathematical analysis of data networks, e.g. social media networks; Analytical and numerical optimisation approaches to real-life systems; Manipulating data and scripting in Python; Data analytics and machine learning; Cluster computing on Hadoop and Spark; Relational and NoSQL databases.
Entry requirements
A minimum of a second class Honours degree, or equivalent, in either a mathematics (joint or single honours) or other numerate subject, e.g. physics. Other degrees will also be taken into account, if it can be shown that some mathematical study took place and you have taken and passed advanced mathematics modules in at least some of calculus, algebra, statistics and numerical analysis. Applicants without these formal qualifications but with significant and appropriate work/life experience are encouraged to apply.
English language requirements
For further information on English Language requirements, please see the university website: https://www.stir.ac.uk/international/international-students/english-language-requirements/
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Sponsorship information
For information on funding and scholarships, please see here: https://www.stir.ac.uk/study/fees-funding/postgraduate-loans-and-funding/
Provider information
University of Stirling
Stirling
FK9 4LA