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deep-learning-bootcamp

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LauzHack Deep Learning Bootcamp

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# Deep Learning Bootcamp

Since 2016, LauzHack has organized hackathons at EPFL in Lausanne, Switzerland. We also organize tech talks during the school year.

This is a repository for our Deep Learning Bootcamp (Summer 2025 Edition). For previous editions, see [Previous Editions](#previous-editions) section.

# Syllabus

- [**day01**](./day01) Introduction to Deep Learning and PyTorch
  - Lecture: Introduction to bootcamp and Deep Learning
  - Seminar: Introduction to `pytorch`
- [**day02**](./day02) Basic Model Architectures
  - Lecture: Fully-connected and Convolutional Neural Networks, ResNet
  - Seminar: Models in `pytorch` and training pipeline
- [**day03**](./day03) Recurrent Neural Networks
  - Lecture: Recurrent Neural Networks, LSTM, GRU
  - Seminar: RNN, LSTM, GRU example
- [**day04**](./day04) Transformer and Normalization layers. Introduction to NLP.
  - Lecture: Transformer. BatchNorm, LayerNorm.
  - Seminar: Implementation of Transformer in `pytorch`
- [**day05**](./day05) Creating convenient Deep Learning pipelines and clean reproducible code.
  - Lecture: Logging, Configuration, Reproducibility, and Project-based code development.
- [**day06**](./day06) Large Language Models (LLMs) and Brain-inspired LLMs.
  - Lecture: Introduction to LLMs and how can we improve them through brain-inspiration.
- [**day07**](./day07) Multimodal deep learning and deep learning for audio.
  - Lecture: Introduction to audio domain. Multimodality and Generative AI. Deepfakes.
  - Seminar: Basics of audio processing. Keyword-spotting task implementation.
- [**day08**](./day08) Source Separation and Deepfake Detection.
  - Lecture 1: Diffusion models, Source Separation
  - Lecture 2: Deepfake Detection, Self-Supervised Models, Graph Neural Networks
  - Seminar 2: Audio anti-spoofing, Graph Neural Networks implementation.

For self-practice, we also propose several [Projects](PROJECTS.md).

# Resources

- [Recordings on YouTube](https://youtube.com/playlist?list=PLpYenI2Zwc7anzzqCBj8KJkyny0xAaUKC)

# Contributors & bootcamp staff

Bootcamp materials and teaching were delivered by:

- Petr Grinberg
- Seyed Parsa Neshaei
- Badr AlKhamissi
- Mingchi (Alina) Hou
- Eric Bezzam (Previously)
- Ali Hariri (Previously)
- Nikita Durasov (Previously)
- Federico Stella (Previously)
- Atli Kosson (Previously)
- Cristian Cioflan (Previously)
- Skander Moalla (Previously)
- Vinitra Swamy (Previously)

# Previous Editions

- [Winter 2025](https://github.com/LauzHack/deep-learning-bootcamp/tree/winter25/)
- [Summer 2024](https://github.com/LauzHack/deep-learning-bootcamp/tree/summer24/)

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