Overview

This course explores the use of AI in the context of GitHub Copilot, a generative AI tool for developers. It equips users with the knowledge and skills to use Copilot effectively while mitigating potential ethical and operational risks associated with AI usage.

Audience Profile

AI developers, engineers, data professionals, business leaders, and policy makers who need to understand GitHub Copilot, its responsible use, and the governance and ethical implications of AI-assisted development.

Syllabus

This module explores the responsible use of AI in the context of GitHub Copilot, a generative AI tool for developers. It will equip you with the knowledge and skills to leverage Copilot effectively while mitigating potential ethical and operational risks associated with AI usage.

Learning Objectives
  • Understand and apply the principles of Responsible AI usage.
  • Identify limitations and mitigate risks associated with AI.
  • Learn best practices for ensuring AI-generated code aligns with ethical standards and project-specific requirements.
  • Recognize the importance of transparency and accountability in AI systems to build trust and maintain user confidence.

GitHub Copilot uses OpenAI Codex to suggest code and entire functions in real time, right from your editor.

Learning Objectives
  • Learn how GitHub Copilot can help you code by offering autocomplete-style suggestions.
  • Learn about the various ways to trigger GitHub Copilot.
  • Learn about the differences among GitHub Copilot Individual, Business, and Enterprise.
  • Learn how to configure GitHub Copilot.
  • Troubleshoot GitHub Copilot.

Discover the essentials of creating effective prompts with GitHub Copilot. Transform coding comments into precise, actionable code to enhance your development workflow and accelerate code delivery.

Learning Objectives
  • Craft effective prompts that optimise GitHub Copilot's performance for precise and relevant code suggestions.
  • Understand the relationship between prompts and Copilot's responses, including best practices such as role prompting and chat history management.
  • Gain insights into how GitHub Copilot handles user prompts, from secure transmission to content filtering and context analysis.

This module introduces Copilot Spaces, guiding developers and PMs to create, configure, and use Spaces effectively for high-quality, grounded responses.

Learning Objectives
  • Explain what Spaces are and when to use them versus general Copilot Chat.
  • Create, configure, and iterate on a Space with targeted context and custom instructions.
  • Apply best practices for high-quality, grounded answers within model context limits.

Use advanced GitHub Copilot features with a Python application.

Learning Objectives
  • Apply slash commands to make code changes.
  • Interact with GitHub Copilot using the Chat feature.
  • Ask questions about your project using an agent.

Explore how to use GitHub Copilot across IDEs, chat, GitHub.com, and the command line to enhance end-to-end development workflows.

Learning Objectives
  • Use Copilot's auto-suggestions and multiple suggestions pane to accelerate development.
  • Provide rich context via comments and documentation to improve Copilot outputs.
  • Use Copilot Chat to generate complex code, debug, and explain implementations.
  • Improve relevance of suggestions using scope referencing, slash commands, and agents.
  • Use Copilot on GitHub.com for repository exploration, pull requests, and issues.
  • Use Copilot in CLI to get explanations, suggestions, and automate terminal workflows.

Explore management and customisation considerations when deploying and governing GitHub Copilot.

Learning Objectives
  • Understand GitHub Copilot plans and related management and customisation features.
  • Gain insight into contractual protections and disabling matching public code.
  • Manage content exclusions effectively.
  • Recognise common problems with GitHub Copilot and how to resolve them.

Explore how GitHub Copilot streamlines developer productivity, impacts the SDLC, and how to measure its benefits and limitations.

Learning Objectives
  • Identify how GitHub Copilot integrates into developer workflows and preferences.
  • Explore Copilot’s impact across stages of the Software Development Lifecycle.
  • Evaluate limitations of AI-assisted coding and measure efficiency gains.

Use GitHub Copilot and Copilot Chat to create and refine unit tests in Visual Studio Code.

Learning Objectives
  • Create unit tests using GitHub Copilot and Copilot Chat in Visual Studio Code.
  • Generate tests targeting edge cases and specific conditions.
  • Use VS Code, .NET SDK, and C# Dev Kit to build and run unit tests successfully.

Learn to build applications using GitHub Copilot Agent Mode with autonomous task execution, documentation-driven guidance, and iterative improvements.

Learning Objectives
  • Develop with VS Code in a GitHub Codespace.
  • Prompt GitHub Copilot agent mode to create an application.
  • Leverage documentation files to direct agent mode.
  • Understand how agent mode iterates to fix errors, refactor, and add features.

Use Copilot coding agent to assign tasks, streamline development, and combine automation with team expertise.

Learning Objectives
  • Explain what the Copilot coding agent is and how it differs from IDE assistants.
  • Describe protections, risks, mitigations, and workflow limits.
  • Assign issues to Copilot, track pull-request sessions, and iterate via @copilot comments.
  • Preconfigure environments, extend capabilities with MCP, and validate output.
  • Apply responsible-use practices, scope tasks, secure environments, and tune performance.

Introduction to GitHub MCP Server and how to integrate it with Copilot Chat for secure, scalable automation.

Learning Objectives
  • Understand what MCP and GitHub MCP Server are and why they are useful.
  • Set up and configure GitHub MCP Server in Visual Studio Code.
  • Use GitHub MCP Server with Copilot Chat to automate development tasks.
  • Identify and resolve common MCP-related issues.

Use GitHub Copilot to enhance code reviews, enforce best practices, and speed up pull request workflows.

Learning Objectives
  • Explain how Copilot streamlines reviews and pull requests.
  • Identify key features Copilot adds to the review process.
  • Request and interpret Copilot reviews on GitHub.com.
  • Run Copilot reviews locally with custom instructions.
  • Use Premium Request Units (PRUs) for deeper analysis.
  • Automate Copilot reviews with rulesets and status checks.
  • Apply suggestions responsibly with human oversight.

Use GitHub Copilot as an AI pair programmer to boost productivity with JavaScript.

Learning Objectives
  • Enable the GitHub Copilot extension in Visual Studio Code.
  • Craft prompts that generate useful suggestions in JavaScript.
  • Use GitHub Copilot to improve a JavaScript project.

Use GitHub Copilot as an AI pair programmer to accelerate Python development.

Learning Objectives
  • Enable the GitHub Copilot extension in Visual Studio Code.
  • Craft prompts that generate useful suggestions in Python.
  • Use GitHub Copilot to improve a Python project.