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AI Enabled Developer Course

Course Overview

This course is designed to provide developers with a comprehensive understanding of GitHub, GitHub Copilot, and responsible AI principles. The course is structured into five main modules plus a capstone project, each focusing on different aspects of using GitHub and GitHub Copilot effectively.

Module 1: Introduction to GitHub & Copilot

  • Learning Objectives: Understand the basics of GitHub and GitHub Copilot, including setup and responsible AI principles.
  • Concept Explanation: This module introduces the GitHub platform, its core features, and how GitHub Codespaces enables faster development.
  • Hands-On Exercises:
    • Open GitHub and create a new repository.
    • Set up GitHub Copilot in your development environment.
  • Code Examples:
    • Example of creating a repository using Git commands.
  • Labs or Mini-Projects:
    • Create a GitHub repository and invite collaborators.
  • Reference Links: GitHub Docs

Module 2: Foundations & Inline Code

  • Learning Objectives: Learn about inline code assistance and master Copilot's core interaction modes (Ask, Edit, Agent) across multiple programming languages.
  • Concept Explanation: This module covers AI code completion, inline code actions, and three primary interaction modes for different development scenarios.
    • Unit 1: AI code completion and inline code actions
    • Unit 2: Ask Mode for learning, Edit Mode for modifications, Agent Mode for autonomous tasks
  • Hands-On Exercises:
    • Use GitHub Copilot to complete code snippets
    • Practice Ask Mode for problem-solving
    • Use Edit Mode for targeted code modifications
    • Leverage Agent Mode for complex multi-file tasks
  • Code Examples:
    • Before vs After improvements using GitHub Copilot
    • Multi-language examples across different modes
    • Integrated workflows combining all three modes
  • Labs or Mini-Projects:
    • Build applications using inline code assistance
    • Create a full-stack Task Management System using all interaction modes
  • Reference Links: GitHub Skills

Module 3: Copilot As Assistant / Conversational Development Workflows

  • Learning Objectives: Understand how to use the Copilot chat interface and context-aware prompting.
  • Concept Explanation: This module explores chat-based development and the importance of context in prompting.
  • Hands-On Exercises:
    • Use the Copilot chat interface to ask for code explanations.
  • Code Examples:
    • Example of using context-aware prompting.
  • Labs or Mini-Projects:
    • Create a project using the Copilot chat interface.
  • Reference Links: Microsoft Learn

Module 4: Copilot Agent Mode

  • Learning Objectives: Get started with Copilot Agent Mode and writing custom instructions.
  • Concept Explanation: This module introduces Agent Mode and how to write effective instructions for agents.
  • Hands-On Exercises:
    • Write custom instructions for a Copilot agent.
  • Code Examples:
    • Example of a prompt file for a Copilot agent.
  • Labs or Mini-Projects:
    • Create a custom agent for a specific task.
  • Reference Links: GitHub Docs

Module 5: Testing with GitHub Copilot

  • Learning Objectives: Learn about AI-based code testing and writing test cases.
  • Concept Explanation: This module covers the importance of testing and how to generate unit tests using GitHub Copilot.
  • Hands-On Exercises:
    • Write unit tests for a given code snippet.
  • Code Examples:
    • Example of generating tests from code.
  • Labs or Mini-Projects:
    • Create a test suite for a simple application.
  • Reference Links: GitHub Skills

Capstone Project: Real-World Application Development

  • Learning Objectives: Apply all learned skills to build a complete, production-ready application using AI-enabled development practices.
  • Concept Explanation: This capstone project synthesizes all previous modules into a comprehensive real-world application, demonstrating mastery of GitHub, GitHub Copilot, and responsible AI principles.
  • Project Requirements:
    • Build a multi-language full-stack application
    • Use AI-assisted development workflow throughout
    • Implement comprehensive test suite with Copilot
    • Apply all 5 Responsible AI principles
    • Create professional documentation
    • Use Agent Mode for complex features
    • Demonstrate context-aware prompting
  • Deliverables:
    • Complete working application
    • GitHub repository with proper structure
    • Comprehensive test coverage
    • README with setup instructions
    • Technical documentation
    • Reflection on AI usage and learnings
  • Reference Links:

Final Output Expectation

Each module will be complete, structured, and ready for commitment to the repository, ensuring technical accuracy and consistent referencing of the curriculum. The capstone project will demonstrate practical application of all course concepts in a real-world scenario.