Deep Learning Bootcamp (Summer 2025)
This is the Summer 2025 edition of our Deep Learning Bootcamp! Join us for these two weeks and master your deep learning skills (even if you start from zero!)! If you want some specific materials, write to us on discord or by email.
Hybrid format: lessons on campus with stream to Zoom and recording. You can be fully remote, fully on campus or you can do some days online and some offline, as you wish.
Participation is free. Registration for the event on Luma is required. Language: English
Join our dl-bootcamp-summer-2025 Discord server channel for announcements and discussions. Time schedule, Zoom link, etc. will be there.
Event description:
DL Bootcamp has two stages:
Introduction to DL – for students with little or no DL background. (July 7rd - 11th)
Advanced specific topics – for those who already know DL or participated in part 1. (July 14th -18th)
The core features of our bootcamp:
Lectures given by PhD experts in the field
Theoretical and practical materials. Both presented in intuitive and easy-to-follow manner, giving you all the necessary information to apply deep learning in your own projects
Beginner-friendly (you can join even if you have zero experience in deep learning)
Discord server with all participants and mentors
No matter if you want to do research work or industry work in the future, you can learn all the necessary skills here
Hybrid Format: lessons on campus and Zoom. All lessons will be recorded
Free, no grade, no credits — no stress self-development
LauzHack participation certificate will be given to all participants
Topics:
Introduction: PyTorch, Deep Learning concept, Datasets, Optimizers, Schedulers, Loss Functions, FC, CNN, RNN, Transformer, Experiment tracking (WandB)
Advanced weeks: Deep Learning for Audio (includes VAE, GANs and Diffusion), TBA (send us your requests)
Guests' Material: TBA
Prerequisites:
Python knowledge: Classes, functions, for-loops, etc.
NumPy would be helpful. Have a look at this lab from COM-202 course to get familiar with the basics. You can also check some of the PyTorch basics here, however, we will go through them.
Lessons format:
Lectures: theory, task description, model architectures, core algorithms for the specific topic, etc.
Seminars: practice, jupyter notebook which will be filled during the class with the mentor, shows how theory looks in practice
Time Schedule:
From 18:00 to 20:00 (may be changed). Monday-Friday. The schedule for each week: will be available in the pinned message on Discord
Check out our previous edition here.
If you have any questions send an email to lauzhack@epfl.ch or contact us in Discord server.