Course Overview
Unlock the power of scientific programming to advance wind resource assessment. This course equips participants with practical skills in Python and its scientific ecosystem—including NumPy, pandas, xarray, and geopandas—as well as QGIS for geospatial data handling. You’ll learn to perform robust numerical wind resource assessments using specialised tools like Windkit and PyWAsP, gaining hands-on experience in processing, analysing, and visualising wind data.
Course Highlights
Ideal for programmers and engineers eager to bridge the gap between software development and renewable energy analytics, this course provides the tools and knowledge needed to contribute effectively to wind energy projects.
MAIN GOAL
Placeholder Text
Learning Outcomes
After completion of this course, you will be able to:
- + Develop and apply scientific programming techniques tailored to wind resource assessment.
- + Use Python and QGIS to process and interpret reanalysis, terrain, and wind measurement datasets.
- + Perform advanced numerical analyses with Windkit and PyWAsP to evaluate wind resources and support wind energy project development.
- + Build a comprehensive understanding of the methodologies, data sources, and best practices fundamental to modern wind resource assessment.
Meet Your Instructors
Researcher
Senior Researcher
Admissions
Entry Requirements
Basic experience with Python and its scientific programming stack.
Basic understanding of wind resource assessment.
Teaching and Assessment Methods
- + Live online sessions
- + Self-paced learning
- + Demonstrations
- + Collaborative troubleshooting
Application Deadline: TBC
Fees & Funding
Tuition Fees
TBC
