How to Master GitHub Copilot in 30 Minutes: A Quick Guide for Developers

If you’re like most developers, you’ve probably heard the buzz about GitHub Copilot but aren’t sure how to make the most of it. You might be wondering, "Can AI really help me code faster, or is it just a gimmick?" In just 30 minutes, I’ll show you how to harness the power of GitHub Copilot effectively, so you can spend less time typing and more time building.

Prerequisites: What You Need to Get Started

Before diving in, make sure you have the following:

1. A GitHub account: You’ll need this to access Copilot.
2. Visual Studio Code (VS Code): Copilot integrates seamlessly with this editor.
3. GitHub Copilot subscription: Pricing starts at $10/month or $100/year for individual developers.

Step 1: Install GitHub Copilot

1. Open Visual Studio Code.
2. Go to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side.
3. Search for "GitHub Copilot" and click the install button.

Expected output: You should see a confirmation that GitHub Copilot is installed.

Step 2: Set Up Your First Project

1. Create a new directory for your project.
2. Open this directory in VS Code.
3. Create a new file (e.g., app.js) and start typing a comment describing what you want to do, like // Create a simple HTTP server.

Expected output: GitHub Copilot will offer suggestions in real-time based on your comment.

Step 3: Use Copilot for Code Completion

As you type, GitHub Copilot will suggest entire lines or blocks of code. You can accept suggestions by pressing Tab.

Example:

• Start typing function fetchData() and see how Copilot fills in the rest.

Troubleshooting: What Could Go Wrong

• Issue: Copilot doesn’t suggest anything.

  • Solution: Make sure you're connected to the internet and logged in to GitHub. Restart VS Code if necessary.

• Issue: Suggestions aren't relevant.

  • Solution: Try providing more context in your comments or function names.

Step 4: Leverage Advanced Features

• Code Explanation: Highlight a piece of code and type // Explain this code. Copilot will generate a comment explaining what the code does.

• Code Translation: Type a comment like // Translate this to Python and see how well it converts your JavaScript to Python.

What's Next: Further Exploration

Now that you’ve set up and used GitHub Copilot, consider exploring these features:

• Pair Programming: Use Copilot to simulate a coding partner.
• Learning New Languages: Experiment with Copilot’s ability to help you code in languages you’re not familiar with.

Conclusion: Start Here

To master GitHub Copilot, dedicate 30 minutes to this guide. Install it, set up a project, and start exploring its features. In our experience, the best way to learn is by doing—so dive in and see how it can accelerate your coding workflow.

Comparison of GitHub Copilot with Other AI Coding Tools

| Tool | Pricing | Best For | Limitations | Our Verdict | |--------------------|-----------------------------|-------------------------------|----------------------------------|-------------------------------------| | GitHub Copilot | $10/mo, $100/yr | Real-time code suggestions | Limited language support | Great for boosting productivity | | Tabnine | Free tier + $12/mo pro | Multi-language support | Less context-aware than Copilot | Good for general coding assistance | | Codeium | Free | Open-source projects | Fewer integrations | Best for budget-conscious developers | | Replit Ghostwriter | $20/mo | Collaborative coding | Limited offline functionality | Good for team projects | | Sourcery | Free tier + $12/mo pro | Python code optimization | Python-specific only | Excellent for Python developers | | Codex | $0-20/mo | Advanced AI features | Requires more setup | Powerful but complex to use |

What We Actually Use

In our stack, we primarily use GitHub Copilot for day-to-day coding tasks. Its real-time suggestions save us hours of work, especially with repetitive tasks. For collaborative projects, we sometimes rely on Replit Ghostwriter.