Welcome to the Weizmann Practical Deep Learning Course 2026
All communication with the lecturers will be made via Slack: click here to join
Your lecturers and TAs are
Etienne Dreyer, Alon Levi, Dmitrii Kobylianskii and Prof Eilam Gross.
The grading system is based on your mandatory homework assignments (10%), a project (<30%), and a final exam (>60%). The exact weight of the project and exam will be fixed so the class average will not exceed 90.
All lecture slides and tutorial code will be posted below. Recordings are available on the Panopto page (TBA).
| Date | Lecture | Material | Block 1 | Material | Block 2 | Material |
|---|---|---|---|---|---|---|
| 16/04/2026 | Eilam: Introduction |
Introduction | Dmitrii Backpropagation |
Etienne: Python, PyTorch & Grad. Desc. |
Tutorial | |
| 23/04/2026 | Eilam: Convolutional NN & architectures |
Keynote Version PDF Version |
Alon: CNNs (tut) |
Tutorial | Dmitrii: Optimization, regularization Homework 1: classification |
|
| 30/04/2026 | Eilam: Detection & Segmentation |
Etienne: UNet |
Tutorial | Etienne: Transfer learning Homework 2: CNNs |
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| 07/05/2026 | Etienne: Autoencoders (VAE) |
PDF Version | Dmitrii: VAE tutorial |
Tutorial | Alon Physics-informed ML |
Tutorial |
| 14/05/2026 | Eilam GAN |
Alon GAN |
Alon GAN Tutorial |
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| 21/05/2026 | No class (Shavuot) | |||||
| 28/05/2026 | Eilam: Graph Neural Networks |
Etienne: GNN tutorial |
Etienne: Homework 3: GNN |
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| 04/06/2026 | Dmitrii: Diffusion |
Dmitrii: Diffusion tutorial |
TBA | |||
| 11/06/2026 | Etienne: Transformers |
TBA: Sequential data |
Dmitrii: Homework 5: attention |
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| 18/06/2026 | Eilam GPT |
Alon Agentic AI |
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| 25/06/2026 | Eilam: Deep Reinforcement Learning |
Dmitrii: Deep Q-learning tutorial |
TBA: Homework 4: policy gradient |
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| 02/07/2026 | Project Proposals I | |||||
| 05/07/2026 | Project Proposals II | |||||
| 06/07/2026 | TBA | |||||
| TBA | Project Presentations (POSTERs festival) |