GH-300: GitHub Copilot

GH-300 Course: GitHub Copilot

GH-300: GitHub Copilot Fundamentals is designed to provide developers with a comprehensive understanding of GitHub Copilot , an AI- powered tool that improves coding efficiency. The course begins with an exploration of responsible AI use, emphasizing the importance of ethical standards, transparency, and accountability in AI systems. Participants will learn how to apply these principles to ensure AI-generated code aligns with specific project requirements and mitigates potential risks.

As the course progresses, students will delve into the various features of GitHub Copilot , including its auto-completion suggestions, chat interface, and integration with different development environments. The course covers practical aspects such as setting up and getting started with GitHub Copilot, troubleshooting common issues, and using advanced features to generate useful code suggestions. Through hands-on exercises, participants will gain experience using GitHub Copilot to improve their coding workflows and increase productivity.

The course also introduces the concept of prompt engineering, teaching participants how to craft effective prompts to optimize GitHub Copilot performance. By understanding data flow and the role of large language models in generating contextual responses, participants will be equipped to take full advantage of GitHub Copilot's capabilities. The course concludes with an overview of applying GitHub Copilot in different programming languages ​​and environments, providing a comprehensive foundation for developers to integrate AI assistance into their daily coding practices.

Intermediate - GitHub - Administrator, DevOps Engineer

Course aimed at

• AI Developers and Engineers: Professionals involved in the creation and deployment of AI systems who need to understand ethical implications and governance frameworks.
• Data scientists and analysts: People who work with data and AI models, focusing on ensuring transparency, fairness, and accountability in their work.
• Business leaders and managers: Decision-makers who oversee AI projects and need to implement responsible AI practices within their organizations.
• Policymakers and regulators: Those responsible for creating policies and regulations around the use of AI, ensuring that AI systems are developed and used ethically and safely.

Course objectives

Upon completion of this course, students will be able to:

• Understand and apply the principles of responsible use of AI.
  
• Configure and troubleshoot GitHub Copilot in various development environments.
  
• Use GitHub Copilot features for code suggestions and completion.
  
• Create effective prompts to optimize GitHub Copilot performance.
  
• Integrate GitHub Copilot into different programming languages ​​and workflows.
  
• Improve coding efficiency and productivity with advanced GitHub Copilot techniques.

Elements of the GH-300 formation

• GitHub Copilot Fundamentals Part 1 (6 modules)
• GitHub Copilot Fundamentals Part 2 (6 modules)
  

GH-300 Course Content

Module 1: Responsible AI with GitHub Copilot

• Mitigate AI risks
• Microsoft and GitHub's six principles of responsible AI

Module 2: Introduction to GitHub Copilot

• GitHub Copilot, your AI pair programmer
• Interact with Copilot
  
• Set up, configure, and troubleshoot GitHub Copilot
  
• Exercise - Develop with AI-powered code suggestions by using GitHub Copilot and VS Code

Module 3: Introduction to prompt engineering with GitHub Copilot

• Prompt engineering foundations and best practices
  
• GitHub Copilot user prompt process flow
  
• GitHub Copilot data
  
• GitHub Copilot Large Language Models (LLMs)

Module 4: Using advanced GitHub Copilot features

• Advanced GitHub Copilot features
• Exercise - Set up GitHub Copilot to work with Visual Studio Code
• Applied GitHub Copilot techniques
• Exercise - Update a web API with GitHub Copilot

Module 5: GitHub Copilot Across Environments: IDE, Chat, and Command Line Techniques

• Code completion with GitHub Copilot
• GitHub Copilot Chat
  
• GitHub Copilot for the Command Line

Module 6: Management and customization considerations with GitHub Copilot

• Explore GitHub Copilot plans and their associated management and customization features
  
• Explore contractual protections in GitHub Copilot and disabling matching public code
  
• Manage content exclusions
  
• Troubleshoot common problems with GitHub Copilot

Module 7: Developer use cases for AI with GitHub Copilot

• Boost developer productivity with AI
  
• Align with developer preferences
  
• AI in the Software Development Lifecycle (SDLC)
  
• Understand limitations and measure impact

Module 8: Develop unit tests using GitHub Copilot tools

• Examine the unit testing tools and environment
  
• Exercise - Create unit tests by using GitHub Copilot Chat
  
• Exercise - Create unit tests for specific conditions by using GitHub Copilot
  
• Exercise - Complete the "create unit tests" challenge
  
• Review the "create unit tests" solution

Module 9: Introduction to GitHub Copilot Business

• About GitHub Copilot for Business
  
• GitHub Copilot for Business use cases and customer stories
  
• How to get started with GitHub Copilot for Business

Module 10: Introduction to GitHub Copilot Enterprise

• About GitHub Copilot Enterprise
  
• How to get started

Module 11: Using GitHub Copilot with JavaScript

• What is GitHub Copilot
• Exercise - Set up GitHub Copilot to work with Visual Studio Code
  
• Use GitHub Copilot with JavaScript
  
• Exercise - Update a JavaScript portfolio with GitHub Copilot

Module 12: Using GitHub Copilot with Python

• What is GitHub Copilot?
  
• Exercise - Set up GitHub Copilot to work with Visual Studio Code
  
• Use GitHub Copilot with Python
  
• Exercise - Update a Python web API with GitHub Copilot

Prerequisites

Students must have:

• Basic knowledge of programming concepts and experience with at least one programming language.
  
• Familiarity with integrated development environments (IDEs) and version control systems such as GitHub.
  
• Basic knowledge of the principles of AI and machine learning.

Language

• Course: English

• Labs: English

Microsoft Certification (To be released in May 2025)

It will be published in May 2025

Level:
Role:
Product:
Subject: Digital & App Innovation