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Deep Learning Course, 2026

Deep Learning Logo

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

Course Staff

  • Eduard Vladimirov @Edyarich
  • Daniil Dorin @DorinDaniil
  • Nikita Kiselev @kisnikser
  • Alexey Kravatskiy @alexlegeartis
  • Vadim Kasiuk @KasiukVadim

Materials

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

Homeworks

Homework # Date Deadline Description Link
1 09.09 30.09 Autograd implementation google form
2 11.10 25.10 Image Captioning google form
3 01.11 15.11 Image Segmentation google form
4 10.11 24.11 Classifier Guidance for Flow Matching google form
5 01.11 13.12 Multi-Armed Bandit + CartPole google form

Game Rules

  • 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)

Prerequisities

  • Probability Theory + Statistics
  • Machine Learning
  • Python

Previous Episodes

  • 2025
  • 2024
  • 2023
  • 2022

About

Intelligent Systems course on Deep Learning

intsystems.github.io/course/deep_learning

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