Data Science Essentials for Wind Energy Systems

Upskill fast—apply data science, AI, and machine learning directly to wind energy challenges, with the option to bring your own project. This is an intensive four-day program designed to meet the pressing demand for advanced digital skills in the evolving wind energy sector. 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.

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. 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.

Nongraded

Engineer and or STEM professionals from the wind energy sector with prior knowledge of data science and foundational knowledge of Python. Requirements: 1. Background in wind energy engineering, data science, or software development. 2. Foundational knowledge of Python programming.