MScApplied Data Science (Renewable Energy)
Source: https://www.exeter.ac.uk/study/postgraduate/courses/mathematics/appdatarenew/ Parent: https://www.exeter.ac.uk/study/postgraduate/courses/
MSc Applied Data Science (Renewable Energy)
MSc Applied Data Science (Renewable Energy)
| UCAS code | 1234 |
| Duration | 1 year full time |
| Entry year | 2026 |
| Campus | Penryn Campus |
| Typical offer View full entry requirements | A good degree (normally a 2:2). |
| Contextual offers |
Why study MSc Applied Data Science (Renewable Energy) at Exeter?
- Become immersed in the ‘Big Data revolution’ and develop state-of-the-art data science and AI skills alongside expertise in emerging renewable technologies
- Based at our stunning Penryn Campus in Cornwall this interdisciplinary programme is run jointly between the departments of Mathematics and Renewable Engineering
- Designed in collaboration with internationally renowned researchers and industrial partners you will benefit from research-led teaching, practical examples and hands-on activities
- Develop sought-after, discipline-transcending skills and utilise these through use of modern scientific computing software and a new state-of-the-art Renewable Engineering Facility
- Gain the skills and experience you need to succeed in the demanding and fast growing data analytics sectors, specifically within renewable technologies.
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Select date of entry Sept 2026
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Fast Track (current Exeter students)
Contact
Programme Director:Dr Markus Mueller
Web: Enquire online
Phone: +44 (0)1392 72 72 72
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Discover MSc Applied Data Science and Renewable Energy at the University of Exeter.
Top 20 in the UK for Mathematics
20th in The Times and The Sunday Times Good University Guide 2026
Top 15 in the UK for General Engineering
13th in the Complete University Guide 2026
Research expertise in climate modelling and statistics; control and dynamics; systems biology; astrophysical fluid flows and number theory
Based on our Penryn Campus in Cornwall, where the UK’s renewable energy revolution began
Entry requirements
A good degree (normally a 2:2).
Successful applicants will usually have at least an A-level or equivalent in Mathematics and/or have received quantitative skills training as part of their undergraduate programme, or possess relevant professional experience.
Prior experience of coding is not necessary on this course.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course.
The required IELTS test scores for this course fall under Profile B1.
Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
The pressing climate crisis has awakened the world to the need for a green technology-enabled revolution. We will expose you to the contemporary research and technologies, guiding you through relevant concepts and trends in data science and modelling and modern methodologies in the fields of AI and Control.
- Term 1: students develop core skills and understanding during the modules in data science and in renewable energy.\ \
- Term 2: students are exposed to state-of-the-art methods in the Trends in Data Science and Artificial Intelligence module, put their data science skills and renewable energy knowledge into practice by completing the interdisciplinary Tackling Sustainability Challenges using Data and Models, and can select options from a suite of Renewable Energy Engineering modules.\ \
- Term 3: students undertake an advanced data science and modelling project
The modules below provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.
Modules
Please note that the module information displayed here is from a previous year and is subject to change.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| EMGM001 | Fundamentals of Data Science | 30 |
| EMGM002 | Trends in Data Science and AI | 15 |
| EMGM003 | Data Science and Modelling Dissertation | 60 |
| EMGM004 | Tackling Sustainability Challenges using Data and Models | 30 |
| ENEM101 | Renewable Energy Systems | 30 |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Select 15 credits*: | ||
| ENEM009 | Advanced Marine Renewable Energy | 15 |
| ENEM011 | Advanced Wind Energy | 15 |
| ENEM012 | Solar Energy Research and Innovation | 15 |
| ENEM105 | Low Carbon Vehicles and Transport | 15 |
| EMGM006 | Applied AI and Control | 15 |
| BEP3172 | Future 17: Sustainable Development Goals Challenge | 15 |
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Markus is the Programme Director and his research addresses mathematical systems and control theory and their applications within marine engineering, renewable energy, systems biology and human wellbeing.
His academic work includes developing the Applied Mathematics programmes for both undergraduate and postgraduate taught students at the Penryn Campus, with a focus on interdisciplinary applications and in close liaison with colleagues.
Read more from Dr Markus Mueller
Dr Markus Mueller
Programme Director
Fees
2026/27 entry
UK fees per year:
£12,900 full-time
International fees per year:
£28,900 full-time
Scholarships
The University of Exeter offers a wide range of scholarships to support your education, with £7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships *. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
University of Exeter Alumni Scholarship
We are pleased to offer University of Exeter alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship towards the cost of your tuition fees. Full details can be found here.
*Terms and conditions, including deadlines, apply. See our website for details..
Find out more about tuition fees and funding »
Teaching and research
We believe every student benefits from being taught by experts active in research and practice. You will discuss the very latest ideas, research discoveries and new technologies in seminars and via using state-of-the-art facilities and software and you will become actively involved in a research project yourself. The programme is led by the Centre for Environmental Mathematics and taught in collaboration with the Renewable Energy Department. You can find out more about our internationally recognised scientific research and industrial, public and charitable sector collaborations at the dedicated web pages for Environmental Mathematics and Renewable Energy.
Facilities
Renewable Energy has access to significant specialist resources and equipment applicable to the renewable energy sector, in addition to the majority of conventional engineering laboratory facilities. Most of our unique facilities relate to ocean energy research, power systems and reliability and field studies. These have relevance both for fundamental research, industrial projects and for teaching purposes.
Graduate School of Environment and Sustainability
You will become part of Exeter's Graduate School of Environment & Sustainability - a vibrant and supportive postgraduate community based here on our Penryn Campus in Cornwall. The Graduate School brings together experts from across the spectrum of earth and life sciences, engineering, humanities, social sciences and business. You will interact with students from other MScs and have the opportunity to explore issues from a range of perspectives, benefiting from a truly interdisciplinary experience. All our programmes are designed with a focus on developing solutions to global challenges and creating a better future for our planet and its people.
Read more
Professor Townley is particularly interested in dynamical systems and control: the study of things (mechanical, biological, electrical, etc.) which interact and evolve in time and can be predicted, managed and optimised.
He’s been the Chair in Applied Mathematics at the Environment and Sustainability Institute (ESI) since June 2011. He works closely with colleagues in the College of Engineering, Mathematics and Physical Sciences, as well as in the College of Life and Environmental Sciences, to understand natural and man-made systems.
Read more from Professor Stuart Townley
Professor Stuart Townley
Professor in Applied Mathematics
Careers
This programme is designed for students from a variety of backgrounds who want to enhance their understanding of and confidence in using real-world data and mathematical models to address the big environmental, social and economic issues of our time, gaining knowledge of local to global scales and tapping into/skilling-up for the “Big Data revolution” in the field and in general.
The UK has one of the world’s strongest and most developed data analytics sectors, predicted to grow by 177% over the next 5 years and demand for qualified professionals continues to grow. The UK’s commitment to expansion of renewable energy is likely to mean a high level of investment in the sector in the next decade. The adoption of the UK’s microgeneration tariff in 2009, the Green Deal in 2013, the phased adoption of the Renewable Heat Incentive from 2011-2014 and introduction of Contracts for Difference in 2014, suggests continued strong support for rapid expansion of renewable energy in the UK.
National and international job opportunities
Internationally, many other countries are making similar investments with major industrial nations including the US, India and China investing heavily in renewable generation. This investment will create broad opportunities for those seeking to work in the sector, both nationally and internationally.
Employer-valued skills
- Data science, modelling and essential programming skills and how to apply these to The United Nations sustainable development goals
- Ability to extract information from data as a basis for evidence-based decision making
- Working with stakeholders and advanced team-working skills in complex organisations
- Using digital media to convert complex data sets into useful information to engage with the lay public and specialists
Students will receive support from our dedicated Career Zone team, who provide excellent career guidance at all stages of career planning. The Career Zone provides one-on-one support and is home to a wealth of business and industry contacts. Additionally, they host useful training events, workshops and lectures which are designed to further support you in following your chosen career path.
Read more
Related courses of interest
The University of Exeter has significant teaching and research interests in the field of Data Science, and is home to the Institute of Data Science and Artificial Intelligence. The Institute of Data Science and Artificial Intelligence (IDSAI) provides a hub for data-intensive science and artificial intelligence (AI) activity within the University and the wider region.
Their vision is to develop innovative approaches to the use of data and artificial intelligence in modern society, covering the entire spectrum from collection through interrogation and analysis, to interpretation, visualisation and communication. They undertake fundamental research in data science and AI and facilitate interactions between data science researchers and problem owners to develop innovative approaches to the use of data in modern society, considering the social implications of data science and AI as well as the technical aspects.
To achieve this they work closely with other researchers, industry and government, for instance with key partners such as the Alan Turing Institute. Students have access to excellent facilities spanning a wide range of machine types and software ecosystems, as well as have the opportunity to study courses at either our Streatham Campus in Exeter or our Penryn Campus in Cornwall.
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