What you’ll learn
Learn to supercharge your development workflow with AI-powered command-line assistance.
Think of it as having a knowledgeable colleague available 24/7 who can read your code, explain confusing patterns, and help you work faster!
This course is designed for:
- Software Developers who want to use AI from the command line
- Terminal users who prefer keyboard-driven workflows over IDE integrations
- Teams looking to standardize AI-assisted code review and development practices
This hands-on course takes you from zero to productive with GitHub Copilot CLI. You’ll work with a single Python book collection app throughout all chapters, progressively improving it using AI-assisted workflows. By the end, you’ll confidently use AI to review code, generate tests, debug issues, and automate workflows: all from your terminal.
No AI experience required. If you can use a terminal, you can learn this.
Perfect for: Developers, students, and anyone who has experience with software development.
Prerequisites
Before starting, ensure you have:
- GitHub account: Create one free
- GitHub Copilot access: Free offering, Monthly subscription, or Free for students/teachers
- Terminal basics: Comfortable with
cd,ls, running commands
Understanding the GitHub Copilot family
GitHub Copilot has evolved into a family of AI-powered tools. Here’s where each one lives:
| Product | Where it runs | Description |
|---|---|---|
| GitHub Copilot CLI (this course) | Your terminal | Terminal-native AI coding assistant |
| GitHub Copilot | VS Code, Visual Studio, JetBrains, etc. | Agent mode, chat, inline suggestions |
| Copilot on GitHub.com | GitHub | Immersive chat about your repos, create agents, and more |
| GitHub Copilot coding agent | GitHub | Assign issues to agents, get PRs back |
This course focuses on GitHub Copilot CLI, bringing AI assistance directly to your terminal.
Course structure
| Chapter | Title | What you’ll build |
|---|---|---|
| 00 | Quick Start | Installation and verification |
| 01 | First Steps | Live demos + three interaction modes |
| 02 | Context and Conversations | Multi-file project analysis |
| 03 | Development Workflows | Code review, debug, test generation |
| 04 | Create Specialized AI Assistants | Custom agents for your workflow |
| 05 | Automate Repetitive Tasks | Skills that load automatically |
| 06 | Connect to GitHub, Databases & APIs | MCP server integration |
| 07 | Putting It All Together | Complete feature workflows |
How this course works
Each chapter follows the same pattern:
- Real-World Analogy: Understand the concept through familiar comparisons
- Core Concepts: Learn the essential knowledge
- Hands-On Examples: Run actual commands and see results
- Assignment: Practice what you learned
- What’s Next: Preview of the following chapter
Code examples are runnable. Every copilot text block in this course can be copied and run in your terminal.
GitHub Copilot CLI command reference
The GitHub Copilot CLI command reference helps you find commands and keyboard shortcuts to help you use Copilot CLI effectively.
Getting help
- Found a bug? Open an Issue
- Want to contribute? PRs welcome!
- Official Docs: GitHub Copilot CLI Documentation
License
This project is licensed under the terms of the MIT open source license. Please refer to the LICENSE file for the full terms.
Video series
Prefer to watch and learn? Follow GitHub’s official Copilot CLI for beginners video series. Pick a chapter below to play it right here on the page.
6 videos in this series