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FRCMIC-16Microsoft

GitHub Copilot (GH-300)

This course introduces developers to GitHub Copilot and demonstrates how AI-assisted coding can improve productivity, code quality, and development efficiency.

Duration · 1 dayVirtual + In-PersonInstructor-Led

$650

Course Description

This course introduces developers to GitHub Copilot and demonstrates how AI-assisted coding can improve productivity, code quality, and development efficiency. Participants will learn how to use Copilot for code generation, debugging, documentation, testing, and refactoring across modern development workflows.

Through hands-on labs and real-world scenarios, students will gain practical experience integrating GitHub Copilot into their daily development activities while following best practices for responsible and secure AI-assisted coding.

— Be First in Line —

Register Your Interest

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Audience Profile

This course is intended for:

  • Software Developers
  • DevOps Engineers
  • QA Engineers
  • Software Architects
  • Technical Leads
  • IT Professionals

Prerequisites

Before enrolling, you should have:

  • Basic programming experience in at least one language (e.g., JavaScript, Python, C#, Java)
  • Familiarity with Git and GitHub workflows
  • Understanding of basic software development concepts (functions, APIs, debugging)

— What You'll Learn —

Learning Objectives

In this course, you will learn to:

  • 1Understand GitHub Copilot capabilities and architecture
  • 2Use Copilot to generate and complete code efficiently
  • 3Improve code quality through AI-assisted suggestions
  • 4Accelerate debugging and troubleshooting workflows
  • 5Generate unit tests and documentation with Copilot
  • 6Refactor and optimize existing codebases
  • 7Apply secure and responsible AI coding practices
  • 8Integrate Copilot into development workflows

— Day-by-Day —

Course Outline

Module 1

Introduction to GitHub Copilot

  • Introduction to AI-Assisted Development
  • What is GitHub Copilot?
  • How GitHub Copilot Works
  • Supported IDEs (Visual Studio Code, Visual Studio, JetBrains)
  • Copilot Chat Overview
  • Benefits of AI in Software Development
  • Limitations of AI Code Generation
  • Responsible AI Considerations
  • Demonstration: GitHub Copilot in Action

Module 2

Getting Started with GitHub Copilot

  • Setting Up GitHub Copilot
  • Authentication and Licensing
  • IDE Configuration
  • Inline Code Suggestions
  • Accepting and Rejecting Suggestions
  • Copilot Shortcuts and Features
  • Using Copilot Chat Interface
  • Best Practices for Setup
  • Hands-On Lab: Installing and Configuring GitHub Copilot

Module 3

Writing Code with GitHub Copilot

  • Prompting in Code Comments
  • Function and Class Generation
  • API Integration Assistance
  • Boilerplate Code Generation
  • Multi-Language Support
  • Code Context Awareness
  • Iterative Code Improvement
  • Writing Effective Prompts in Code
  • Hands-On Lab: Building a Small Application with Copilot

Module 4

Debugging and Code Improvement

  • Understanding Copilot Debug Suggestions
  • Identifying Bugs and Errors
  • Explaining Existing Code
  • Improving Code Structure
  • Performance Optimization Suggestions
  • Refactoring Legacy Code
  • Error Handling Improvements
  • Code Review Assistance
  • Hands-On Lab: Debugging and Refactoring Code with Copilot

Module 5

Testing and Documentation with Copilot

  • Test-Driven Development with Copilot
  • Generating Unit Tests
  • Writing Integration Tests
  • Edge Case Identification
  • Code Documentation Generation
  • README and API Docs Creation
  • Improving Test Coverage
  • Maintaining Test Quality
  • Hands-On Lab: Creating Tests and Documentation Using Copilot

Module 6

GitHub Copilot Chat and Advanced Features

  • Introduction to Copilot Chat
  • Asking Complex Coding Questions
  • Code Explanation and Analysis
  • Multi-Step Problem Solving
  • Architecture Suggestions
  • Refactoring Assistance
  • Working with Multiple Files
  • Advanced Developer Workflows
  • Hands-On Lab: Solving Development Tasks with Copilot Chat

Module 7

Secure and Responsible AI Coding Practices

  • Responsible AI in Software Development
  • Secure Coding Guidelines
  • Avoiding Sensitive Data Exposure
  • Reviewing AI-Generated Code
  • Licensing and Intellectual Property Considerations
  • Bias and Code Quality Risks
  • Human-in-the-Loop Development
  • Organizational Coding Standards
  • Discussion: Responsible AI Scenarios in Development

Module 8

Productivity Optimization and Best Practices

  • Developer Workflow Integration
  • Pair Programming with AI
  • Improving Code Consistency
  • Team Collaboration with Copilot
  • Version Control Best Practices
  • Managing Large Codebases
  • Measuring Productivity Gains
  • Continuous Learning Strategies
  • Workshop
  • Optimizing a Real Development Workflow
  • Capstone Exercise: Build an Application Using GitHub Copilot
  • Capstone Exercise: Participants will build a small functional application using GitHub Copilot assistance throughout the development lifecycle.
  • Activity: Design application structure
  • Activity: Generate core application code
  • Activity: Implement features using Copilot
  • Activity: Create unit tests
  • Activity: Debug and refactor code
  • Activity: Document the application
  • Activity: Present final solution

— The Big Picture —

Key Takeaways

  • GitHub Copilot fundamentals and setup
  • AI-assisted coding techniques
  • Debugging and refactoring with AI
  • Test and documentation generation
  • Secure and responsible coding practices
  • Advanced Copilot Chat usage
  • Developer productivity optimization

— What You'll Walk Away With —

Skills Gained

  • AI-assisted software development
  • Code generation and optimization
  • Debugging and troubleshooting with AI
  • Automated testing and documentation
  • Secure and responsible coding practices
  • Developer workflow optimization

— Next Steps —

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