2h lecture: references and concepts on neural networks and DL
2h lecture: Graph Neural Networks
2h lecture: Attention and Transformers
2h lecture: Generative models

hands-on 1 ~3h: implementation and application of a GNN to an interesting physics problem
hands-on 2 ~3h: implementation and application of a Transformer for example to do jet-tagging at the LHC
hands-on 3 ~3h: implementation and application of a generative model for example based on normalizing flow or on a diffusion model