GitHub Copilot Cert Prep by Microsoft Press
6h 1mIntermediate2025-05-05
Authors
Microsoft Press
Microsoft
Tim Warner
Technical Trainer and Content Developer
Course details
Accelerate your journey to becoming a certified GitHub Copilot expert with this comprehensive course. Tim Warner, a generative AI expert and Microsoft Certified Trainer, guides you through essential topics like responsible AI usage, Copilot features across all SKUs, and data security. Understand how to effectively configure GitHub Copilot for different environments, ensuring secure and ethical development practices. Explore prompt engineering techniques to maximize Copilot's suggestions. Learn how to boost your code quality by integrating advanced testing capabilities and AI-driven insights into your development flow. Dive into real-world practical lessons and interactive demos that prepare you not only for the GitHub Copilot certification exam but also for practical application in professional settings. This course helps you master the skills you need to prepare for the GitHub Copilot Certification exam and make the most of the potential of AI in software development.
Skills covered
Github CopilotVersion ControlGitHubGenerative AIArtificial Intelligence FoundationsSoftware Development ToolsCert PrepArtificial Intelligence (AI)Software Development
Concepts
0. Introduction
- 01 - Introducing the course
1. Explain the Responsible Usage of AI
- 02 - Learning objectives
- 03 - Learn the risks associated with using AI tools in software development
- 04 - Learn the limitations of generative AI
- 05 - Discover why validating AI-generated code is essential for quality and security
- 06 - Identify best practices for responsibly operating AI tools
- 07 - Mitigate potential harms, such as bias and insecure code
- 08 - Define ethical AI principles and how they apply to GitHub Copilot
2. Identify the Features of GitHub Copilot Individual
- 09 - Learning objectives
- 10 - Learn the available features in the integrated development environment (IDE) for GitHub Copilot Individual
- 11 - Identify the main differences between GitHub Copilot Individual and Business
- 12 - Configure GitHub Copilot settings for individual users
3. Identify the Features of GitHub Copilot Business
- 13 - Learning objectives
- 14 - Exclude specific files from GitHub Copilot suggestions
- 15 - Establish organization-wide policy management for AI usage
- 16 - Learn the purpose and use of organization audit logs to monitor GitHub Copilot activity
- 17 - Manage GitHub Copilot Business subscriptions via the REST API
4. Identify the Features of GitHub Copilot Enterprise
- 18 - Learning objectives
- 19 - Learn the benefits of using GitHub Copilot Enterprise for large-scale development teams
- 20 - Get familiar with GitHub Copilot knowledge bases
- 21 - Create and manage knowledge bases to improve code quality, consistency, and efficiency
- 22 - Identify the benefits of using custom models for enhanced AI code suggestions
5. Identify the Main Features of GitHub Copilot Chat
- 23 - Learning objectives
- 24 - Identify the key use cases where GitHub Copilot chat is most effective
- 25 - Share feedback about Copilot chat to improve its performance
- 26 - Learn best practices for Copilot chat, including available slash commands
- 27 - Learn the limitations of GitHub Copilot chat
6. Describe How GitHub Copilot Handles Data
- 28 - Learning objectives
- 29 - Learn how GitHub Copilot processes data for code suggestions
- 30 - Learn how GitHub Copilot uses and shares data for individuals and businesses
- 31 - Identify the different input types Copilot processes and how they affect the output
- 32 - Explain the data flow for GitHub Copilot chat and Copilot IDE integrations
7. Describe the GitHub Copilot Data Pipeline Lifecycle
- 33 - Learning objectives
- 34 - Visualize the lifecycle of a GitHub Copilot code suggestion
- 35 - Learn how GitHub Copilot gathers context and builds a prompt
- 36 - Learn about the role of proxy services and filtering mechanisms in Copilot s data pipeline
- 37 - Discover how the large language model generates and post-processes responses
8. Describe the Limitations of GitHub Copilot
- 38 - Learning objectives
- 39 - Learn how frequent examples in source data affect code suggestions
- 40 - Discover how the age of source data affects the relevance of suggestions
- 41 - Identify the challenges of limited context windows in Copilot s prompt handling
9. Use GitHub Copilot in the Command-Line Interface (CLI)
- 42 - Learning objectives
- 43 - Learn the steps for installing GitHub Copilot in the CLI
- 44 - Identify common commands and their use cases when working with GitHub Copilot in the CLI
- 45 - Configure settings within GitHub Copilot for CLI usage
10. Describe Prompt Engineering and Prompt Crafting Fundamentals
- 46 - Learning objectives
- 47 - Learn the fundamentals of prompt engineering
- 48 - Learn the structure and key components of an effective prompt
- 49 - Identify best practices for crafting prompts to maximize Copilot s output quality
- 50 - See how GitHub Copilot prompts use chat history
11. Improve Developer Productivity with GitHub Copilot
- 51 - Learning objectives
- 52 - See common use cases where GitHub Copilot enhances productivity
- 53 - Learn how Copilot aids in managing the software development lifecycle
- 54 - Use the GitHub Copilot productivity API to measure impact
12. Enhance Code Quality Through Testing
- 55 - Learning objectives
- 56 - Learn how GitHub Copilot can assist in generating unit tests, integration tests, and edge case tests
- 57 - Learn how Copilot identifies potential edge cases and suggests test improvements
- 58 - Write assertions and boilerplate code for various test types using Copilot
13. Leverage GitHub Copilot for Security and Performance
- 59 - Learning objectives
- 60 - Learn how GitHub Copilot identifies potential security vulnerabilities in code
- 61 - Learn how Copilot can suggest performance optimizations
- 62 - See how Copilot supports collaborative code reviews with security best practices
14. Describe the Different SKUs for GitHub Copilot
- 63 - Learning objectives
- 64 - Identify the available SKUs for GitHub Copilot, including its Individual, Business, and Enterprise plans
- 65 - Understand the privacy considerations for each SKU
- 66 - Learn the configuration options for code suggestions at the organization level
15. Identify Content Exclusions
- 67 - Learning objectives
- 68 - Configure content exclusions at the repository and organization level
- 69 - Understand the effects and limitations of content exclusions on Copilot s suggestions
- 70 - Learn about ownership considerations for GitHub Copilot outputs
16. Explain the GitHub Copilot Safeguards
- 71 - Learning objectives
- 72 - Learn about Copilot s duplication detection filter
- 73 - Understand the contractual protections available for Copilot users
- 74 - Enable and disable duplication detection, prompt collection, and suggestion collection settings
17. Troubleshoot GitHub Copilot
- 75 - Learning objectives
- 76 - Resolve common issues, such as missing code suggestions in the editor
- 77 - Identify troubleshooting steps when context exclusions do not apply as expected
- 78 - Trigger GitHub Copilot when suggestions are absent or suboptimal
18. Review for the GitHub Copilot Certification
- 79 - Learning objectives
- 80 - Recap key concepts
- 81 - Work through sample exam questions
- 82 - Learn test-taking strategies and tips for success
19. Explore the Future of AI-Powered Development
- 83 - Learning objectives
- 84 - Learn the upcoming trends in AI-assisted development
- 85 - Identify new features and future updates expected in GitHub Copilot
- 86 - Understand the importance of continued learning and skill development in AI-driven software engineering
Conclusion
- 87 - Look back on what you've learned