| Date | Week | Topic | Resources | Homework assignment |
|---|---|---|---|---|
| 24.9.2025 | 1 | Intro: Introduction to the course and machine learning. | Classification | |
| 1.10.2025 | 2 | 1D regression and 2D classification: Revision of the regression and classification theory, analytic gradient computation, gradient in computational graph and loss minimization. | template_for_students.zip labs_02_regression.pdf | |
| 8.10.2025 | 3 | Loss, MLP | HW01 - MLP | |
| 15.10.2025 | 4 | Autograd: Computational graphs, backpropagation and the automatic gradient computation. | lab04.zip lab04.pdf lab04_ref.zip | |
| 22.10.2025 | 5 | Labs cancelled (ICCV 2025) | HW01 deadline | |
| 29.10.2025 | 6 | CNN: Introduction to convolution and convolution neural networks | lab05.zip lab05_ref.zip | HW02 - Autograd |
| 5.11.2025 | 7 | Training of neural networks | lab06.zip lab06_solved.zip | |
| 12.11.2025 | 8 | Layers of Neural Networks | lab7.zip | HW02 deadline HW03 - segmentation |
| 19.11.2025 | 9 | Optimization: Convergence rate, oscillations, diminishing gradients. | lab8.zip | |
| 26.11.2025 | 10 | Transformers I: Introduction to the transformer architecture, GPT2 | lab10.zip | |
| 3.12.2025 | 11 | Transformers II: Intro into ViTs | HW03 deadline HW04 - Transformers | |
| 10.12.2025 | 12 | RL I Intro: Introduction to the reinforcement learning. Policy gradient. | rl_lab_1.pdf | |
| 17.12.2025 | 13 | RL II - Deep learning: Deep reinforcement learning. | HW04 deadline HW05 - RL | |
| 7.1.2026 | 14 | HW05 deadline |