About the Course
This course will equip wind engineers with a range of statistical, data-driven tools and methodologies that enable advanced analytics and insight extraction from operational wind turbine data. The course builds upon basic data science techniques and introduces more advanced concepts specifically focused on challenges related to wind farm operation and maintenance.
After this course, you can
Apply data science techniques—including uncertainty quantification, advanced statistical analysis and testing, machine learning model training and evaluation, feature engineering, and sequence modelling—to wind energy data.
Process and analyse SCADA data for wind turbine operations.
Design, implement, and train anomaly detection algorithms tailored to specific detection tasks in wind energy applications.
Design, implement, and test virtual sensing solutions for monitoring and control purposes.
Implement and operate probabilistic prognostic models to estimate reliability and failure frequencies, including time between failures.
6 weeks, online/hybrid, part-time
1. Solid understanding of the wind energy sector and wind turbine design or engineering processes, typically gained through a master’s degree in wind energy or equivalent industry experience.
2. Familiarity with Python programming.
3. Basic knowledge of data science and statistics, equivalent to what is covered in an introductory data science course.
The course uses a problem-based learning approach. Participants receive an introductory package with multiple datasets and a series of related problem exercises, each accompanied by study materials and supported by explanatory lectures. In the final stage, participants present their results and justify their chosen methodologies. Both synchronous and asynchronous teaching methods are used.
Evidence your learning with a Certificate of Achievement from the DTU on successful completion.
This course will be stackable with other LLL courses that will be developed by DTU Wind, to form certain specialisations or micro-degrees. For instance, we offer a series of courses that can be combined to form the specialisation “Data-Driven Decision Making for Wind Farm Operations.” This specialisation includes four courses, with “Model-Based Estimation of Remaining Useful Life” serving as the entry point.
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.
Nikolay Dimitrov
Senior Scientist
Nikolay Dimitrov is a Senior Scientist in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). He is an expert in wind turbine reliability, structural health monitoring, and uncertainty quantification, with a focus on developing advanced digital twins and...
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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.
Financing Options
We offer a range of discounts and packages to make the programme more accessible.
Early Bird Discount
Register before 01 December
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20%
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10%
Off
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Team-Based Learning
Enroll a group of 3 or more participants from the same company and benefit from special team pricing.
Boost collaboration and apply knowledge directly in your workplace.
Join with your team
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For course-specific questions, please contact the course responsible Nikolay Dimitrov, Senior Scientist at DTU Wind, nkdi@dtu.dk
Didn't find what you were looking for? Or need a customised training solution for your company? Contact Karsten Kryger, Coordinator of Lifelong Learning at DTU Wind, kkry@dtu.dk