- Copyright 2025
- Edition: 1st
-
Online Video
- ISBN-10: 0-13-542463-1
- ISBN-13: 978-0-13-542463-6
6+ hours of video training
Boost productivity and validate expertise as you prepare to pass the GitHub Copilot Certification
GitHub Copilot Cert Prep is designed to equip learners with the skills and knowledge needed to make the most of GitHub Copilot, culminating in a certification that validates their expertise. As coding becomes more complex and projects more demanding, tools like Copilot are essential for boosting productivity and maintaining high code quality. Understanding how to effectively use Copilot is crucial for developers who want to stay competitive and efficient in today's fast-paced tech environment.
The course begins with an overview of GitHub Copilot's core features, followed by in-depth, step-by-step screencasts that guide you through real-world scenarios. The course is authored by Tim Warner, a seasoned professional with extensive experience in GitHub Copilot and a strong background in teaching these concepts.
About the Instructor:
Tim Warner has been a Microsoft MVP in Azure AI and Cloud/Datacenter Management for 6 years and a Microsoft Certified Trainer for more than 25 years. His O'Reilly Live Training classes on generative AI, GitHub, DevOps, data engineering, cloud computing, and Microsoft certification reach hundreds of thousands of students around the world. He's written for Microsoft Press, presented at Microsoft Ignite, and contributed to several Microsoft open-source projects. You can connect with Tim on LinkedIn: timw.info/li.
Skill Level:
Learn How To:
- Use Responsible AI
- Utilize GitHub Copilot plans and features
- Use GitHub Copilot's work and data handling
- Prompt crafting and prompt engineering
- Develop use cases for AI
- Test with GitHub Copilot
- Implement privacy fundamentals and context exclusions
Course requirements:
Pre-requisites:
- Basic programming experience
- Familiarity with Git and GitHub workflows
- Understanding of software development lifecycle
- Experience with Integrated Development Environments (IDEs)
Who Should Take This Course:
Job titles:
- Software Developers
- Junior Developers
- DevOps Engineers
Associated code is available:
https://github.com/timothywarner/copilot-cert-prep
About Pearson Video Training:
Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.
Table of Contents
Introduction
Lesson 1: Explain the Responsible Usage of AI
1.1 Learn the risks associated with using AI tools in software development
1.2 Learn the limitations of generative AI
1.3 Discover why validating AI-generated code is essential for quality and security
1.4 Identify best practices for responsibly operating AI tools
1.5 Mitigate potential harms, such as bias and insecure code
1.6 Define ethical AI principles and how they apply to GitHub Copilot
Lesson 2: Identify the Features of GitHub Copilot Individual
2.1 Learn the available features in the IDE for GitHub Copilot Individual
2.2 Identify the main differences between GitHub Copilot Individual and Business
2.3 Configure GitHub Copilot settings for individual users
Lesson 3: Identify the Features of GitHub Copilot Business
3.1 Exclude specific files from GitHub Copilot suggestions
3.2 Establish organization-wide policy management for AI usage
3.3 Learn the purpose and use of organization audit logs to monitor GitHub Copilot activity
3.4 Manage GitHub Copilot Business subscriptions via the REST API
Lesson 4: Identify the Features of GitHub Copilot Enterprise
4.1 Learn the benefits of using GitHub Copilot Enterprise for large-scale development teams
4.2 Get familiar with GitHub Copilot Knowledge Bases
4.3 Create and manage Knowledge Bases to improve code quality, consistency, and efficiency
4.4 Identify the benefits of using custom models for enhanced AI code suggestions
Lesson 5: Identify the Main Features of GitHub Copilot Chat
5.1 Identify the key use cases where GitHub Copilot Chat is most effective
5.2 Share feedback about Copilot Chat to improve its performance
5.3 Learn best practices for Copilot Chat, including available slash commands
5.4 Learn the limitations of GitHub Copilot Chat
Lesson 6: Describe How GitHub Copilot Handles Data
6.1 Learn how GitHub Copilot processes data for code suggestions
6.2 Learn how data is used and shared by GitHub Copilot Individual and Business
6.3 Identify the different input types Copilot processes and how they impact the output
6.4 Explain the data flow for GitHub Copilot Chat and Copilot IDE integrations
Lesson 7: Describe the GitHub Copilot Data Pipeline Lifecycle
7.1 Visualize the lifecycle of a GitHub Copilot code suggestion
7.2 Learn how GitHub Copilot gathers context and builds a prompt
7.3 Learn about the role of proxy services and filtering mechanisms in Copilot's data pipeline
7.4 Discover how the large-language model generates and post-processes responses
Lesson 8: Describe the Limitations of GitHub Copilot
8.1 Learn how frequently seen examples in source data affect code suggestions
8.2 Discover how the age of source data impacts the relevance of suggestions
8.3 Identify the challenges of limited context windows in Copilots prompt handling
Lesson 9: Use GitHub Copilot in the Command Line Interface
9.1 Learn the steps for installing GitHub Copilot in the CLI
9.2 Identify common commands and their use cases when working with GitHub Copilot in the CLI
9.3 Configure settings within GitHub Copilot for CLI usage
Lesson 10: Describe Prompt Engineering and Prompt Crafting Fundamentals
10.1 Learn the fundamentals of prompt engineering
10.2 Learn the structure and key components of an effective prompt
10.3 Identify best practices for crafting prompts to maximize Copilot's output quality
10.4 See how chat history is used in GitHub Copilot prompts
Lesson 11: Improve Developer Productivity with GitHub Copilot
11.1 See common use cases where GitHub Copilot enhances productivity
11.2 Learn how Copilot aids in managing the Software Development Lifecycle
11.3 Use the GitHub Copilot Productivity API to measure impact
Lesson 12: Enhance Code Quality Through Testing
12.1 Learn how GitHub Copilot can assist in generating unit tests, integration tests, and edge case tests
12.2 Learn how Copilot identifies potential edge cases and suggest test improvements
12.3 Write assertions and boilerplate code for various test types using Copilot
Lesson 13: Leverage GitHub Copilot for Security and Performance
13.1 Learn how GitHub Copilot identifies potential security vulnerabilities in code
13.2 Learn how Copilot can suggest performance optimizations
13.3 See how Copilot supports collaborative code reviews with security best practices
Lesson 14: Describe the Different SKUs for GitHub Copilot
14.1 Identify the available SKUs for GitHub Copilot, including Individual, Business, and Enterprise
14.2 Understand the privacy considerations for each SKU
14.3 Learn the configuration options for code suggestions at the organization level
Lesson 15: Identify Content Exclusions
15.1 Configure content exclusions at the repository and organization level
15.2 Understand the effects and limitations of content exclusions on Copilot's suggestions
15.3 Learn about the ownership considerations for GitHub Copilot outputs
Lesson 16: Explain the GitHub Copilot Safeguards
16.1 Learn about Copilot's duplication detection filter
16.2 Understand the contractual protections available for Copilot users
16.3 Enable and disable duplication detection, prompt collection, and suggestion collection settings
Lesson 17: Troubleshoot GitHub Copilot
17.1 Resolve common issues, such as missing code suggestions in the editor
17.2 Identify troubleshooting steps when context exclusions do not apply as expected
17.3 Trigger GitHub Copilot when suggestions are absent or suboptimal
Lesson 18: Review for the GitHub Copilot Certification
18.1 Recap key concepts
18.2 Work through sample exam questions
18.3 Learn test-taking strategies and tips for success
Lesson 19: Explore the Future of AI-Powered Development
19.1 Learn the upcoming trends in AI-assisted development
19.2 Identify new features and future updates expected in GitHub Copilot
19.3 Understand the importance of continued learning and skill development in AI-driven software engineering
Summary