MSc Data Science for Renewable Energy
Key Details
- Attendance
- Full Time
- Award
- Degree of Master of Science
- Course Length
- 1 year
- Course Start Date
- September 2025
Course Overview
On this dynamic MSc in Data Science for Renewable Energy, you’ll gain cutting-edge skills that place you at the forefront of this rapidly growing industry.
Data science skills are highly valuable in the field of renewable energy across a wide range of areas. These include the prediction and forecasting of renewable energy resource and system performance, renewable energy data analytics, design and optimisation of renewable energy systems, and monitoring and diagnostics of renewable energy systems. Data science also plays a crucial role in energy storage and building energy management systems. The combination of specialised data science and renewable energy technical skills is highly sought after both in research and development and the renewable energy industrial sector.
This interdisciplinary course will give you an excellent practical and theoretical grounding in Python programming and data mining. In parallel, you'll develop skills in engineering and technical aspects of renewable energy covering solar energy, wind energy and energy from water currents and wave motions, while using international databases and applying statistical analysis and modelling techniques. You'll acquire professional skills for data scientists, while also having the opportunity to develop further skills in Artificial Intelligence and information visualisation or more technical skills in electrical grid data analysis, energy storage, and power systems.
Studying at UEA places you at the heart of a booming renewable energy sector, surrounded by a diverse range of engineering companies. You’ll benefit from these industry links from the very start of your course. You’ll also have access to industry-standard facilities in Productivity East, and frequent opportunities to showcase your potential to industry professionals, through events like our annual Select Partnership Scheme.
After graduation, you’ll be well equipped to explore a wide range of career opportunities in the ever-expanding renewable energy sector, where the demand for skilled data science professionals continues to rise.
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Study and Modules
Structure
This MSc in Data Science for Renewable Energy course is a full-time, one-year taught programme, designed for advanced students and practitioners.
On this course, you’ll study Python programming, data mining and renewable energy topics such as solar energy, wind energy and energy from water currents and wave motions. You'll also explore how data science techniques can be used to analyse renewable energy data. In parallel, you'll develop professional skills for data scientists and you'll have the option to develop further skills in Artificial Intelligence, information visualisation, or power systems including the analysis of electrical grid data.
A key element of the course is your dissertation, which is a research project involving extensive independent study using data science methods in a renewable energy problem (which may be with an industry partner), under the supervision of a faculty member.
Compulsory Modules
Optional A Modules
(Credits: 20)Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, the University will endeavour to consult with students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will inform students.
Teaching and Learning
You’ll have an average of 15 hours of contact time per week with teaching staff, depending on your module choices. This will include lectures, seminars and lab classes. The seminars and lab classes will reinforce and expand on the lecture material. The course has both theoretical and practical elements, so you’ll get hands-on experience in data mining software, and the use of international databases and tools for the analysis of renewable energy data and the design and performance analysis of renewable energy systems.
Your individual study time (around 25 hours per week) will complement the formal teaching and will support the development of your skills and expertise in data analysis and renewable energy.
Your dissertation will further develop your research skills and extend the practical data science and engineering skills you’ll have developed throughout the course. Your dissertation is an exciting opportunity to implement data science techniques in a renewable energy research project of your choice.
Assessment
You’ll have a mixture of individual and group assessments including written assignments, presentations or demonstrations, tests and exams. These combine theory with practical application and are designed to test the range of skills and competencies required for the learning outcomes of each module. The balance of assessment types varies according to the options you choose. The dissertation is assessed through a dissertation report and presentation.
Entry Requirements
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical UK Entry Requirements
Degree classification
Bachelors degree - 2.2.
Degree Subject
Engineering, Computing, Mathematics, Physics, Environmental Sciences or related subject areas. Strong applicants from other backgrounds with experience relevant to Environmental Sciences, Energy Engineering or Data Science are also encouraged to apply.
- Additional Entry Requirements
Academic Technology Approval Scheme (ATAS)
Applicants applying for a Student VISA may require an ATAS certificate before they apply for their visa. Check the ATAS Government website to see if you will require an ATAS certificate. Please note the Government are taking several weeks to process ATAS requests, so please ensure you request clearance in good time. If you have any questions please contact pgt.admissions@uea.ac.uk.
- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical International Entry Requirements
Degree classification
Bachelors degree - 2.2 or equivalent
Degree Subject
Engineering, Computing, Mathematics, Physics, Environmental Sciences or related subject areas. Strong applicants from other backgrounds with experience relevant to Environmental Sciences, Energy Engineering or Data Science are also encouraged to apply.
- Additional Entry Requirements
Academic Technology Approval Scheme (ATAS)
Applicants applying for a Student VISA may require an ATAS certificate before they apply for their visa. Check the ATAS Government website to see if you will require an ATAS certificate. Please note the Government are taking several weeks to process ATAS requests, so please ensure you request clearance in good time. If you have any questions please contact pgt.admissions@uea.ac.uk.
- English Foreign Language
Applications from students whose first language is not English are welcome. We require evidence of proficiency in English (including writing, speaking, listening and reading):
-
IELTS: 6.0 overall (minimum 6.0 in Writing and Speaking, and 5.5 in Reading and Listening)
We also accept a number of other English language tests. Review our English Language Equivalencies for a list of example qualifications that we may accept to meet this requirement.
Test dates should be within two years of the course start date.
If you do not meet the English language requirements for this course, INTO UEA offer a variety of English language programmes which are designed to help you develop the required English skills.
-
- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
Fees and Funding
Tuition fees for the Academic Year 2025/26 are:
-
UK Students: £11,775
-
International Students: £24,500
We estimate living expenses at £1,136 per month.
Further Information on tuition fees can be found here.
Scholarships and Bursaries
The University of East Anglia offers a range of Scholarships; please click the link for eligibility, details of how to apply and closing dates.
Course Related Costs
Please see Additional Course Fees for details of course-related costs.
How to Apply
How to apply
Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.
To apply please use our online application form.
Application deadline
International applicants and non UK Nationals may require an ATAS certificate, depending on individual circumstances. In order to allow sufficient time to apply and receive an ATAS certificate, international applications will close on 11/07/2025.
Further information
If you would like to discuss your individual circumstances prior to applying, please do contact us:
Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk
International candidates are also encouraged to access the International Students section of our website.
Employability
After the Course
You'll graduate well-equipped to pursue various career opportunities in the renewable energy industry, including roles as a data analyst, data scientist, data miner, machine learning engineer, research scientist, or consultant, among others. The course also provides a solid foundation if you're interested in continuing your studies towards a PhD in the renewable energy field.
Careers
Examples of careers that you could enter include:
- Renewable energy systems, design, operation & maintenance
- Energy management
- Power network
- Data scientist
- Data analyst
- Data miner
Discover more on our Careers webpages.
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