🔥 Deep Learning with PyTorch

From raw tensors and autograd to a trained, exported, served model — the canonical PyTorch 2.x path, built by hand.

9-day mini-course — From raw tensors and autograd to a trained, exported, served model — the canonical PyTorch 2.x path, built by hand.

Like every course on this site, each day is a deep, code-first lesson: an intuition-first explainer, a staged code walkthrough explaining the methodology line by line, visuals, and a 🧪 Your task exercise with a hidden solution. Theory lives in the AI & ML Encyclopedia; here you build.

▶ Start Day 1   📚 All mini-courses

Syllabus

Day	Lesson
Day 1	Tensors & Autograd: The Foundation
Day 2	Building Models with nn.Module
Day 3	Feeding the Model: Dataset & DataLoader
Day 4	The Training Loop, Properly
Day 5	Classification End to End: An MLP on Real Data
Day 6	Convolutional Networks: Teaching Models to See
Day 7	Training Deeper Networks: Stability & Regularization
Day 8	Transfer Learning: Stand on ImageNet’s Shoulders
Day 9	Saving, Exporting & Serving Your Model