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
| Resource | Link |
|---|---|
| Official MiniTorch | GitHub |
| MiniTorch Documentation | minitorch.github.io |
| YouTube Recordings | Playlist |
| Google Classroom | Join |
| Meet Link | Join Call |
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)