Lifelong Learning Module
Data Science Essentials for Wind and Energy Systems
Upskill fast—apply data science, AI, and machine learning directly to wind energy challenges, with the option to bring your own project.
Join the course’s free masterclass webinar on 26 May. Register here to reserve your spot.
About the Course
This is an online three weeks program designed to meet the pressing demand for advanced digital skills in the evolving wind energy sector. Delivered as a guided learning journey, the course combines self-paced learning with daily 2 hours live sessions for interaction. Participants will gain expertise in key topics, including research data management, data visualisation, machine learning, and AI applications, all tailored to wind energy and delivered through practical Python programming. The course blends theoretical lectures from leading voices in industry and academia - with interactive, hands-on exercises and a capstone project. Participants are also encouraged to bring their own data and projects to tackle practical challenges directly relevant to their work. This approach ensures that participants acquire both conceptual knowledge and immediately applicable skills for real-world wind energy analysis and decision-making.
Key learning areas encompass the full spectrum of digital best practices: data visualisation, metadata management (including industrial FAIR principles, data ontologies, and labelling), basic statistics, exploratory data analysis, data processing, and feature engineering. Participants will also explore machine learning and AI methods, versioning with Git (supported by pre-course video material), as well as licensing and the wider regulatory framework shaping data use in the wind energy sector.
By integrating the latest industry developments and leveraging deep expertise, this lifelong learning module empowers you to upskill rapidly and meet the evolving needs of the wind energy sector.
Course Highlights
Here are the key highlights of the program, designed to give you a clear picture of what sets this course apart and how it can strengthen your expertise in wind energy.
Enhance Digital Skills
Gain essential data science expertise tailored for the wind energy sector.
Practical Application
Apply theory through hands-on exercises and real-world case studies.
Industry Relevance
Stay current with the latest trends and technologies in wind energy and data science.
Collaborative Learning
Build teamwork skills through group projects and interactive sessions.
Innovation in Wind Energy
Develop innovative thinking and problem-solving for data management and analysis challenges in the wind industry.
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After this course, you can
Explain foundational concepts in data science and research data management, and discuss their application within wind energy systems.
Apply key Python libraries to perform common data science tasks, following best practices for data analysis and visualization in wind energy contexts.
Apply machine learning algorithms to address sector-specific challenges in wind energy.
Analyse datasets using statistical methods and acritically evaluate the performance of data-driven models.
Design and present a capstone project that applies your data science skills to solve real-world wind energy problems.
15 June - 3 July 2026
The course runs over 3 weeks, with an estimated time commitment of approximately 15 hours per week.
Each week is structured around a balanced mix of self-paced learning and live interactive sessions, allowing participants to combine flexibility with guided teaching from expert teachers. Self-paced activities such as short video lectures, demonstrations, readings, and quizzes can be completed at a time that suits your schedule, while live sessions are scheduled at fixed times to support hands-on learning, discussion, and collaboration.
This format is designed to be compatible with full-time professional work, while still providing sufficient depth and continuity to build practical data science skills that can be applied in wind energy contexts.
1. Background in wind energy engineering, data science, or software development.
2. Foundational knowledge of Python programming.
The course is delivered in an online format as a guided learning journey, combining self-paced learning with daily 2 hours live sessions for interaction to increase flexibility while maintaining a strong interactive learning experience.
Self-paced and time-flexible learning components include:
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Short, focused, recorded video lectures introducing key concepts and methods
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Curated reading materials and examples tailored to wind energy applications
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Online quizzes and practical exercises to reinforce learning and support self-assessment
Synchronous live sessions focus on application and interaction. These sessions include:
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Hands-on coding exercises in Python
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Guided walkthroughs of real-world wind energy datasets
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Break-out room activities for peer discussion and collaborative problem-solving
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Opportunities for live Q&A with teachers
To accommodate a global participant audience, each live session is offered in two time slots covering the same content:
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First session: 9:00 CET (serving participants in Asia–Pacific, Europe, and Africa)
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Second session: 15:00 CET (serving participants in Europe and the Americas)
All core learning materials are available online throughout the course, enabling participants to revisit content and learn at their own pace and time. Communication and course support are facilitated the learning platform, fostering ongoing dialogue between participants and teachers.
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Participants who successfully complete the course will receive a Certificate of Achievement from DTU. For those wishing to formalise their learning further, an optional assessed project (pre-defined by the course teachers) is available, upon completion of which participants will be awarded a 2.5 ECTS micro-credential from DTU.
This course will be stackable with other LLL courses that will be developed by DTU Wind, to form certain specialisations or micro-degrees.
Key Information
Meet your teacher
Learn from world-class researchers and passionate educators who bring cutting-edge expertise and hands-on experience into the classroom.
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Vasilis Pettas
Postdoctoral Researcher
Vasilis Pettas is a Postdoctoral Researcher in the Department of Wind and Energy Systems at DTU, where he works on data-driven methods for wind farm operation, control, and structural load assessment. His research combines wind turbine and wind farm modelling with...
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Mohit Sharma
Senior Vice Presiden at Marubeni Corporation
Singapore
“Solid and comprehensive overview!”
"For anyone considering a career transition, this course offers a solid and comprehensive overview of wind energy. It equips you with the essential knowledge and skills needed to smoothly transition into the wind energy field."
Sophie Yin
Renewables Engineer, Woodside Energy
Australia
“Flexible learning with outstanding support!”
“What I enjoy the most about the programme is the flexibility. I have been able to access the content around other aspects of my life, which has been very valuable. Also, the lecturers have made them available to the students online to answer questions and actually provide knowledge beyond the course, which I really enjoyed.”
Fahd Outailleur
Head of Engineering at Enel Green Power
Morocco
“Europe’s leader in wind energy”
“I chose to enrol in this wind energy master's program because DTU is the leading technical university in Europe, renowned for its specialization in wind energy. The program reflects the state of the art of the sector. Before joining, I knew some of their software programmes like WAsP and the Global Wind Atlas. So I was confident about the quality of the training.”
DTU Student Testimonials
Discover what DTU students have to say about their journey, their experiences, and the skills they’ve gained.
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Financing Options
We offer a range of discounts and packages to make the programme more accessible.
Early Bird Discount
Register before November 1st
Save
20%
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Bring a Colleague
Sign up together with a colleague and you’ll both receive
10%
Off
Invite your friends
Team-Based Learning
Enroll a group of 3 or more participants from the same company and benefit from special team pricing.
Join with your team
Early Bird Discount
Register before 20th Sep
Save
20%
Save 20%
Bring a Colleague
Sign up together with a colleague and you’ll both receive
Save
20%
Save 20%
Early Bird Discount
Register before 20th Sep
Save
20%
Save 20%
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Register here
For course-specific questions or if you are looking for a customised training solution for your company, please contact us at courses@windenergy.dtu.dk.
Pre-register here
For course-specific questions or if you are looking for a customised training solution for your company, please contact us at courses@windenergy.dtu.dk.