Learn GitHub Copilot by Example

GitHub Copilot by Example — a hands-on, example-driven course that teaches practical Copilot workflows, real-world code patterns, and productivity best practices to accelerate your development. Moreover, this introduction doubles as the meta description for SEO and quick previews.

Course Overview

This course uses short, focused examples so you learn by doing. Firstly, you will understand how Copilot suggests code and how to steer suggestions safely. Secondly, you will discover practical tricks to integrate Copilot into your daily workflows in VS Code and other supported editors. Furthermore, you will build multiple mini-projects that show Copilot assisting with tests, refactors, documentation, and debugging. Consequently, you’ll finish with real skills that you can apply immediately.

What You’ll Learn

• How Copilot generates and suggests code completions in context.
• Prompting techniques to get safer and more relevant suggestions.
• Using Copilot for unit tests, refactoring, and documentation.
• Integrating Copilot into VS Code, GitHub Codespaces, and CLI workflows.
• Best practices for reviewing, editing, and securing AI-generated code.
• Real-world mini-projects illustrating feature-specific usage.

Course Content & Structure

The course divides into concise modules with code-first examples. Each module contains short videos, downloadable code snippets, and guided exercises. Additionally, we include quizzes to reinforce learning and a final capstone mini-project to demonstrate integrated Copilot usage across coding, testing, and documentation. Also, every lesson links to recommended reading and sample repositories so you can practice independently.

Requirements

• Basic knowledge of at least one programming language (JavaScript, Python, or TypeScript recommended).
• An active GitHub account to try Copilot features (optional but recommended).
• A code editor such as Visual Studio Code (free) with extension installation permissions.
• Willingness to experiment and review generated code critically.

Learning Outcomes

After completing this course you will confidently use Copilot to speed up routine tasks, write better tests, and produce cleaner code. Moreover, you will be able to evaluate AI suggestions, adapt prompts for higher-quality output, and apply safety checks to generated code. Ultimately, you’ll become a more productive developer who leverages Copilot intelligently rather than passively.

Explore These Valuable Resources.

• Official GitHub Copilot overview
• GitHub Copilot documentation
• Copilot extension on Visual Studio Marketplace

Explore Related Courses

Find more courses that complement this one; follow the tags below to explore extended learning paths.

• Explore Related Courses
• Explore Related Courses
• Explore Related Courses
• Explore Related Courses
• Explore Related Courses

About This Publication

The course author is a seasoned software engineer and technical instructor who focuses on developer productivity and modern tooling. Furthermore, they have led workshops on AI-assisted development for teams and contributed examples to open-source projects. Consequently, the course balances practical demos with responsible guidance on using AI in codebases.

Format & Extras

The course includes downloadable code samples, step-by-step transcripts, and suggested projects for practice. Also, you will receive lifetime access to updates and community Q&A resources so you can stay current as Copilot evolves.

Buy With Confidence

If you want hands-on, example-based learning that improves your daily coding, this course delivers. Moreover, we recommend starting with the introductory modules and then moving to language-specific examples to maximize your learning speed.