Summer School: Data Science & AI for Energy Engineers

This course offered a unique opportunity to analyze, forecast, and optimize energy flexibility and demand using data science and artificial intelligence techniques. The course focused on practical use cases in the energy sector, providing a comprehensive introduction to data science with a hands-on approach. Participants learned how to use Python and other tools to analyze and visualize energy demand data, as well as how to share their results with stakeholders using advanced dashboards.

Throughout the course, students gained practical knowledge of state-of-the-art tools for monitoring and experimenting with energy datasets. They explored the limitations of machine learning models and their reliance on time series and statistical principles to forecast energy demand. Participants also learned how to optimize the behavior of energy flexible resources using arbitrary cost functions and tracked their experiments using cutting-edge tools.