Phase 3: Frameworks & Debugging · ~75 minutes · Python

Introduction to PyTorch

You built the engine from pistons and crankshafts. Now learn the one everyone actually drives.

What you will learn

Build and train neural networks using PyTorch's nn.Module, nn.Sequential, and autograd
Use PyTorch tensors, GPU acceleration, and the standard training loop (zero_grad, forward, loss, backward, step)
Convert your from-scratch mini framework components to their PyTorch equivalents
Profile and compare training speed between your pure-Python framework and PyTorch on the same task

Introduction

Type: Build
Languages: Python
Prerequisites: Build Your Own Mini Framework
Time: ~75 minutes

Objective

Learning objectives

Build and train neural networks using PyTorch's nn.Module, nn.Sequential, and autograd
Use PyTorch tensors, GPU acceleration, and the standard training loop (zero_grad, forward, loss, backward, step)
Convert your from-scratch mini framework components to their PyTorch equivalents
Profile and compare training speed between your pure-Python framework and PyTorch on the same task

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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