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Git is like a save system for your code. It tracks every change you make, lets you go back to any previous version, and makes it easy to collaborate with other developers. GitHub is where you store your Git projects online — think of it as Google Drive, but purpose-built for code. As an AI engineer, you’ll use Git constantly: to back up your work, to experiment with new ideas without breaking what already works, and to download open-source AI tools and models that other developers have shared. Learning Git isn’t optional — it’s a foundational professional skill.

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Why you need Git

Working with AI projects without Git leads to painful problems:
  • Lost code — Overwrite something that was working and have no way to get it back
  • Broken experiments — Change your script and forget what the original looked like
  • No portfolio — No public record of the projects you’ve built
  • Missed tools — Most AI libraries and examples are shared as GitHub repositories
Git solves all of these problems, and it takes less than 30 minutes to get started.

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What you’ll cover

This Git section is intentionally focused. You only need about five or six commands to be productive with Git, so you’ll learn exactly those — nothing more:
  • Understanding version control (5 minutes)
  • Creating a GitHub account (5 minutes)
  • Cloning and creating projects (10 minutes)
  • Using Git inside VS Code (10 minutes)
This guide keeps things simple on purpose. You don’t need to understand branching strategies or rebasing right now. Master the basics first — the advanced stuff will make sense later.

What Is Version Control?

Understand snapshots, commits, and the core Git workflow in 5 minutes

GitHub Setup

Create your GitHub account and connect it to Git on your machine

Clone and Create

Download existing projects and publish your own to GitHub

VS Code Git

Commit, push, and pull using VS Code’s built-in visual Git tools