University of Glasgow - Open Day
18 Jun 2026, 08:00
Glasgow
The Masters in Data Analytics for Economics & Finance is multi-disciplinary programme that prepares you for data-driven careers in economics and finance. It combines insights from economics, finance, statistics, and computing science. With a focus on rigorous data methods, graduates gain essential skills to inform complex decision-making. Jointly delivered by the Adam Smith Business School and the School of Computing Science, the programme provides you with future-proof, in-demand expertise for today’s fast-changing industries.
WHY THIS PROGRAMME
The programme will build on your strong interest in data analytics to develop their skills in using data rigorous methods in order to inform complex decision making, using big data.
This programme offers a distinctive and innovative multi-disciplinary approach to the field of data analytics as applied to economics and finance, comprising core and elective courses offered from the Departments of Economics, Accounting & Finance, and Computing Science.
You will complete advanced training in order to develop data analytic skills in preparation for successful careers in business or industry.
The programme also provides a solid foundation for PhD study.
You will have the opportunity to participate in summer project internships with some of our prestigious partners.
You can gain recognition for extra-curricular activities by joining the Adam Smith Business School’s Graduate Award Scheme.
The programme is ranked in the top 70 of the QS World University Business Masters Ranking 2026.
Experience practical learning with real business challenges. Network, collaborate, and make a real-world impact through competitive, merit-based industry projects.*
*Industry Projects are not guaranteed. All applications are subject to availability and review processes. We will support candidates with their applications before the deadline but if unsuccessful, they can opt for a research proposal for their dissertation. Students can also secure their own projects with approval from academic and/or professional services.
PROGRAMME STRUCTURE
This programme will provide advanced training in time series analysis, panel data econometrics and Bayesian inference, based on internationally-recognised research to equip you to apply their knowledge and skills to conduct state-of-the-art research to lead and deliver projects.Pre-sessional courses ensure that students from different backgrounds can catch up to the required level of pre-requisite knowledge.
You will take four course courses and a selection of optional courses. Over the summer months you will also complete a dissertation, either under the standard research pathway, or as part of an internship with one of our indsutry partners.
Pre-sessional courses
Computational Statistics and Data Analytics
Econometrics and Statistics Review
Core courses
Applied Time Series and Forecasting
Bayesian Data Analysis
Microeconometrics: Impact Evaluation and Causal Analysis
Statistical Machine Learning
Optional courses
Applied Computational Finance
Asset Pricing: Theory and Empirics
CyberSecurity Fundamentals for MSc (M)
Data Science for Marketing Analytics
Deep Learning for MSc (M)*
Financial Information Retrieval
Text as Data for MSc*
Research project
Dissertation DAEF Industry Pathway or Dissertation DAEF Research Pathway
*Students who choose either of those optional courses, must also select Programming & Systems Development (offered in semester one) as a pre-requisite.
International applicant information can be found via gla.ac.uk by searching for 'international'.
Discover what it's like to study Data Analytics for Economics & Finance at University of Glasgow: insights on the course, making friends, personal statement tips, uni prep, and recommended books, podcasts, and videos.
2.1 Hons (or non-UK equivalent) in Economics, Finance, Computing Science or another subject with a quantitative focus.
Additional documents required when applying for this programme:
Personal statement.
Please address the questions below in no more than 500 words:
why you have applied for this programme,
the relevant experience you have to support your application,
how you think the programme will benefit you in the future.
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.
All fees are published on the University of Glasgow website.
https://www.gla.ac.uk/postgraduate/feesandfunding/
Sponsorship and funding information can be found via gla.ac.uk by searching for 'scholarships'.
At University of Glasgow