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Repository files navigationDeep Learning Course, 2026
This course provides a comprehensive exploration of modern deep learning techniques, from foundational concepts to advanced topics.
- Introduction to Neural Networks: MLP, Backpropagation, Initialization, Optimization, Regularization, CNN
- Natural Language Processing: Word Embeddings, RNN, LSTM, Attention, Transformer, LLM, Agents
- Computer Vision: Classification, Object detection, Segmentation
- Generative Models: Autoregression, VAE, GAN, Diffusion, Diffusion Models, Flow Matching, Multimodality
- Advanced: Reinforcement Learning, Deep Learning Theory, Acceleration
| Week # |
Date |
Topic |
Lecture |
Seminar |
Recording |
| 1 |
September, 8 |
MLP, Backpropagation |
lecture |
seminar |
record |
| 2 |
September, 15 |
Optimization, Regularization |
lecture |
seminar |
record 2025 |
| 3 |
September, 22 |
Initialization, Normalization, CNN |
lecture |
seminar, notes |
TBA |
| 4 |
September, 29 |
Intro to NLP, Word Embeddings |
lecture |
seminar |
record |
| 5 |
October, 6 |
RNN, LSTM, Attention, Transformer |
lecture |
seminar |
record |
| 6 |
October, 13 |
LLM, Fine-Tuning, LoRA, RAG, Agents |
lecture |
NONE |
record |
| 7 |
October, 20 |
Classification, Object Detection |
lecture |
seminar |
lecture, seminar |
| 8 |
October, 27 |
Segmentation, Style transfer |
lecture |
seminar1, seminar2 |
lectute, seminar |
| 9 |
November, 3 |
Autoregression, VAE, GAN |
lecture |
seminar |
record |
| 10 |
November, 10 |
Diffusion Models, Flow Matching |
lecture |
seminar |
record |
| 11 |
November, 17 |
TBA |
TBA |
TBA |
TBA |
| 12 |
November, 24 |
TBA |
TBA |
TBA |
TBA |
| 13 |
December, 1 |
TBA |
TBA |
TBA |
TBA |
| 14 |
December, 8 |
TBA |
TBA |
TBA |
TBA |
- 14 Quizzes = 14 points
- 5 Homeworks = 50 points
- Oral Exam = 40 points
- Maximum Points: 14 + 50 + 40 = 104 points
Final Grade: min(round(#points/10), 10)
- Probability Theory + Statistics
- Machine Learning
- Python
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