GitHub Copilot Certification Bootcamp

GitHub Copilot is an AI-powered code development tool designed to streamline software creation by leveraging a Large Language Model (LLM) trained on public GitHub repositories. It offers developers intelligent code suggestions and completions, enhancing productivity and code quality.

This comprehensive training course is tailored for software developers aiming to master GitHub Copilot and prepare for the GitHub Copilot Certification exam. Participants will gain hands-on experience and in-depth knowledge to effectively integrate Copilot into their development workflows and confidently approach the certification process.

Key takeaways from this class include:

Understanding GitHub Copilot:

  • Explore the core functionalities and underlying mechanisms of Copilot.
  • Learn how Copilot integrates with various Integrated Development Environments (IDEs).
  • Understand the distinctions between GitHub Copilot Individuals, GitHub Copilot Business, and GitHub Copilot Enterprise.

Prompt Engineering Techniques:

  • Develop skills to craft effective prompts that yield accurate and relevant code suggestions.
  • Practice refining prompts to address complex coding challenges.

Utilizing Copilot Features:

  • Gain proficiency in using inline code suggestions to accelerate development.
  • Explore advanced features such as Copilot Chat, Copilot Docs, and Copilot for Pull Requests.
  • Learn to automate unit test generation and other testing processes using Copilot.

Collaborative Development Practices:

  • Understand how to effectively use Copilot in team environments, including enterprise workflows.
  • Leverage Copilot to enhance code reviews and pair programming sessions.

Ethical and Security Considerations:

  • Address ethical concerns related to intellectual property and code originality.
  • Ensure compliance with coding standards and protect sensitive information when using Copilot.

Certification Exam Preparation:

  • Align course content with the GitHub Copilot Certification exam objectives.
  • Engage in practice scenarios and assessments to build confidence and readiness for the exam.

Practical Applications:

  • Gain practical experience creating unit test projects and running unit tests in Visual Studio Code.
  • Learn about specific use cases and customer stories for GitHub Copilot Business and Enterprise.

By completing this course, developers will be equipped with the necessary skills and knowledge to effectively utilize GitHub Copilot in their projects and achieve certification, demonstrating their proficiency in this innovative tool.

Who Should Attend:
This course is designed for software developers, QA engineers, and technical leads who want to:

  • Improve their coding efficiency and quality using AI-assisted development tools.
  • Incorporate GitHub Copilot into their development or testing workflows.
  • Prepare for the GitHub Copilot Certification exam to validate their expertise.
  • Explore advanced AI-driven capabilities for enterprise-level software development.

GitHub Copilot Certification Exam
This course prepares you for the GitHub Copilot exam. The GitHub Copilot certification exam evaluates your skill in using the AI-driven code completion tool in various programming languages, certifying your capability to optimize software development workflows efficiently. Learn more about GitHub certifications here.

Course Outline

Responsible AI

  • Understanding ethical AI principles
  • Identifying risks, limitations, and biases in generative AI tools
  • Validating AI outputs and ensuring fairness, privacy, and transparency
  • Strategies to mitigate harms from AI use

GitHub Copilot Plans and Features

  • Overview of Copilot plans: Individual, Business, Enterprise
  • Key features in IDEs and differences between plans
  • Introduction to Copilot Chat and its best practices
  • Using Copilot for code suggestions, pull requests, and knowledge bases
  • Managing Copilot Business policies, subscriptions, and audit logs
  • Integrating Copilot into the command line interface (CLI)

How GitHub Copilot Works and Handles Data

  • Data flow and lifecycle of code suggestions
  • How Copilot gathers context and builds prompts
  • Role of proxy services and filters in data processing
  • Limitations of Copilot and considerations for data security

Prompt Crafting and Engineering

  • Fundamentals of effective prompt creation
  • Contextualizing prompts for accurate suggestions
  • Best practices in zero-shot and few-shot prompting
  • Optimizing chat history for improved interactions

Developer Use Cases for AI

  • Enhancing developer productivity with AI
    • Learning new languages and frameworks
    • Debugging, modernizing legacy applications, and refactoring
  • Applications in SDLC management and data science
  • Addressing limitations in AI-assisted workflows

Testing with GitHub Copilot


  • Automating unit, integration, and other test types with Copilot
  • Using Copilot to identify edge cases and improve test coverage
  • Incorporating Copilot’s features into test-driven development (TDD)

Privacy Fundamentals and Context Exclusions

  • Understanding privacy implications in Copilot’s operations
  • Excluding sensitive files and defining context limits
  • Organizational privacy policies for enterprise users

Class Daily Schedule

Sign-In/Registration 7:30 - 8:30 a.m.
Morning Session 8:30 a.m. - 12:00 p.m.
Lunch 12:00 - 1:00 p.m.
Afternoon Session 1:00 - 5:00 p.m.
Times represent the typical daily schedule. Please confirm your schedule at registration.

Training Course Fee Includes

• Digital course materials
• Continental breakfasts and refreshment breaks
• Lunches