Course Overview
This five-day intensive course covers essential data science topics tailored for the wind energy sector. It combines theoretical lectures, hands‑on exercises, and a capstone project to provide participants with practical skills directly applicable to their work. Key areas include research data management, data visualization, machine learning, and AI applications specific to wind energy problems using Python programming.
Course Highlights
The course features guest speakers from industry and academia, offering insights into current trends and challenges in the field. Participants will learn to handle data, perform statistical analysis, implement machine learning algorithms, and apply these skills to decision‑making processes in a wind energy context.
MAIN GOAL
To equip engineering professionals, data scientists, and researchers in the wind energy sector with advanced digital skills for data analysis and management, enabling them to address current industry challenges and drive innovation.
Learning Outcomes
Upon completion, graduates will have a core understanding of:
- + Data analysis
- + Machine Learning
- + Statistical Methods
- + Data Visualisation
- + Research Data Management
- + AI applications in Wind Energy
MEET YOUR INSTRUCTORS
Admissions
Entry Requirements
Basic Python programming skills.
Teaching and Assessment Methods
- + Lectures
- + Hands-on exercises
- + Guest Speaker Sessions
- + Group Projects
- + Capstone Project Presentation
Application Deadline: TBC
Fees & Funding
Tuition Fees
TBC
Scholarships Available
- + Green Future Scholarship – Merit-based financial aid for top applicants.
- + Women in Renewable Energy – Supports female students in STEM fields.
- + Industry-Sponsored Fellowships – Partnership grants from energy companies.
Career Prospects
Career Opportunities
Graduates can pursue roles such as:
Renewable Energy Engineer
(Solar, Wind, Biomass, Hydro)
Energy Systems Analyst
Sustainability Consultant
Grid Integration Specialist
Project Manager (Clean Energy Sector)