GitHub Copilot

This comprehensive learning path guides you through GitHub Copilot, from foundational concepts to advanced AI-powered development techniques. Master responsible AI practices, prompt engineering, agent modes, and language-specific implementations.

Part 1:

1. Responsible AI

Master responsible AI use and mitigate ethical risks.

1. Mitigate AI risks

2. Microsoft and GitHub's six principles

2. Introduction

Uses AI to suggest code and functions in real-time.

1. AI-powered pair programming partner

2. Interacting with suggestions

3. Install, configure, and troubleshoot

3. Introduction to Prompt Engineering

Learn to create effective prompts that transform comments into code.

1. Basics and best practices of prompt engineering

2. User prompt process flow

3. Data sources and privacy

4. Large Language Models (LLM)

4. Copilot Spaces

Learn to create and configure Spaces for better AI responses.

1. Creating your first space

2. Sharing, discovery, and governance

3. Good and bad practices for working in a space

5. Advanced Features

Use advanced features with a Python application.

1. Advanced features

2. Applied techniques

6. Across Environments

Use across IDEs, command line, and GitHub.com.

1. Code completion

2. Chat

3. On GitHub.com

4. Command Line

7. Management and Customization

Explore management and customization options.

1. Explore plans and management features

2. Contractual protections and disabling matching

3. Manage content exclusions

4. Troubleshoot common problems

8. Developer Use Cases

Discover how it boosts developer productivity and SDLC.

1. Boost developer productivity with AI

2. Align with developer preferences

3. AI in the Software Development Lifecycle (SDLC)

4. Understand limitations and measure impact

9. Develop Unit Tests

Create unit tests using Chat tools.

1. Examine the unit testing tools and environment

2. Create unit tests using the Generate Tests smart action

3. Create unit tests using Inline Chat

4. Create unit tests using Chat view modes

Part 1: GitHub Copilot Concepts

Responsible AI

Prompt Engineering

Copilot Spaces

Code Completion

Copilot Chat

Inline Chat

VS Code

Command Line

LLM

OpenAI Codex

Generate Tests

Unit Testing

Productivity

SDLC

Content Exclusions

PRUs

GitHub Copilot main concepts covered in Part 1

Part 2:

1. Building Applications with Agent Mode

Build apps with Agent Mode for autonomous development.

1. What is Agent Mode?

2. Explore the power of autonomous development assistance

2. Accelerate Development with Coding Agent

Use coding agent to assign tasks and streamline development.

1. Understanding and enabling the coding agent

2. Security, risks, and limitations

3. Assigning, tracking, and troubleshooting tasks

4. Customizing, extending, and validating

5. Responsible use on GitHub.com

3. Introduction to MCP Server

Integrate GitHub MCP Server with your AI tools and Chat.

1. Simplify your AI workflow with GitHub MCP Server

2. Configure, connect, and use GitHub MCP Server in VS Code

3. Using MCP Server with Chat

4. Knowledge check

4. Leveling Up Code Reviews and Pull Requests

Enhance code reviews with AI-powered assistance.

1. What it adds to the review process

2. Using as a reviewer in GitHub.com

3. Catching issues early and automating reviews

4. Measuring impact and optimizing premium request units (PRUs)

5. Using with JavaScript

Use with JavaScript for AI-powered code suggestions.

1. What is it?

2. Use with JavaScript

6. Using with Python

Use with Python for AI-powered code suggestions.

1. What is it?

2. Use with Python

Part 2: GitHub Copilot Concepts

Agent Mode

Coding Agent

MCP Server

Code Reviews

Pull Requests

JavaScript

Python

GitHub Copilot main concepts covered in Part 2

Each module contains practical exercises, code examples, and hands-on tutorials to help you master AI-assisted development with GitHub Copilot effectively.