Active Program Repository — All resources used and created during the MiniTorch learning program sessions. This repository is continuously updated as we progress through each module.
Currently in: Module 0 (ML Programming Foundations)
MiniTorch is a pure Python re-implementation of PyTorch's API, designed to be simple, easy-to-read, tested, and incremental. It enables students to understand how deep learning frameworks work from the ground up through hands-on assignments.
- Module 0: ML Programming Foundations
- Module 1: Autodifferentiation (Derivatives & Backpropagation)
- Module 2: Tensors & Broadcasting
- Module 3: GPUs & Parallel Programming
- Module 4: Foundational Deep Learning (Convolution, Pooling, Classification)
- YouTube Playlist: Watch all recordings
- Google Classroom: Join the class
- Video Call Link: Google Meet (All Sessions)
- Sunday: 8:00 PM – 10:00 PM
- Wednesday: 8:00 PM – 10:00 PM
| Module | Topic | Assignment Link |
|---|---|---|
| Module 0 | ML Programming Foundations | GitHub Classroom |
| Module 1 | Autodifferentiation | Coming Soon |
| Module 2 | Tensors | Coming Soon |
| Module 3 | GPUs & Parallel Programming | Coming Soon |
| Module 4 | Foundational Deep Learning | Coming Soon |
This repository contains:
- 📓 Jupyter Notebooks — Python fundamentals and reference materials
- 🐍 Python Scripts — Code examples and demonstrations for each module
- 🎬 Session Recordings — Links to recorded sessions in YouTube Playlist
- 📊 Presentations — Slide decks used during sessions
- 📝 Session Notes — Meeting minutes and key discussion points
- 📄 Reference Materials — Supporting PDFs and documentation
Comprehensive Python learning materials organized by topic:
-
Python Basics (in
Jupiter-Notebooks/)- Python Functions
- Python Data Structures
- Python OOP & Exceptions
-
Python Scripts (in
Python-Scripts/)- Module-0 — ML Programming Foundations (coming soon)
- Module-1 — Autodifferentiation (coming soon)
- Module-2 — Tensors & Broadcasting (coming soon)
- Module-3 — GPUs & Parallel Programming (coming soon)
- Module-4 — Foundational Deep Learning (coming soon)
- Resources for Modules 1-4 will be added as the program progresses
This is an internal project of the School of AI Algiers Club (SOAI Labs) at ESI. For questions or contributions, please reach out to the course organizers.
- Attend Sessions: Join us every Sunday and Wednesday at 8:00 PM - 10:00 PM on Google Meet
- Access Resources: Browse this repository for notebooks, slides, and materials used in sessions
- Watch Recordings: If you miss a session, review the YouTube Playlist
- Join Classroom: Register in Google Classroom for announcements and updates
- Complete Assignments: Submit your work through the Module Assignment Links
- Check Back: Check back regularly as new content will be added each week
Last updated: March 2026 | Program Status: Active (Module 0)