Data Science and AI for Energy Engineers

Throughout the course, students will gain practical knowledge of state-of-the-art tools for monitoring and experimenting with energy datasets. They will also explore the limitations of machine learning models and how they rely on time series and statistical principles to forecast energy demand. Participants will learn how to optimize the behavior of energy flexible resources using arbitrary cost functions, tracking their experiments using cutting-edge tools. Students will also learn about the opportunities and limitations of foundational models, including LLMs, in the energy sector.

Why this course on energy data science?

Energy data science gives you the tools to:

• Be able to ask better questions about energy data and answer them.
• Understand the industrial context in which these data science algorithms are applied.
• Possess practical skills to load, explore, analyse and visualise various energy datasets.
• Be able to make energy demand forecasts using machine learning models, while also understanding their limitations and how they build on time series and statistical principles.
• Know how to optimise the behaviour of energy flexible resources given arbitrary cost functions, ranging from minimising costs to grid peaks and carbon emissions.
• Be able to track your experiments using state-of-the-art tools.
• Be able to present the results of your analysis in a manner accessible to both specialists and non-specialists.
• Explore opportunities and limitations of foundational models, including LLMs, in the energy sector.