What are you going to learn?
The energy transition calls for the smart use of artificial intelligence. Grid operators and other organisations in the energy sector face the challenge of making AI not only technically sound, but also sustainable, transparent, and practically applicable. Radboud University and Alliander have co-created a training programme that directly addresses these sector-wide needs.
The programme consists of three days of in-depth study and application, each with its own theme:
- Model choice – how to select the right AI model for specific situations.
- PINNs in practice – introduction, functioning, and training of Physics-Informed Neural Networks.
- Sustainable and explainable AI – the impact of LLMs, energy usage, and methods to visualise predictions in an accessible way.
By the end of the course, participants will have:
- Skills to select the right AI model for a given application.
- Understanding of Physics-Informed Neural Networks (PINNs) and how to train them.
- Awareness of AI sustainability issues, including the impact of large language models and energy use.
- Tools to make AI predictions transparent and explainable to end-users, such as technicians.
