Passing the GitHub Copilot Certification: A Study Guide

Passing the GitHub Copilot Certification: A Study Guide

As an early adopter of GitHub Copilot, I took and passed the Beta version of the GitHub Copilot Certification Exam in August, and with the general availability of the exam coming up in October, I wanted to share my insights and a comprehensive study guide to help others interested in taking the GitHub Copilot certification test.

My Experience with the Exam

While I’ve been using Copilot with VS Code professionally for over a year, I was initially caught off guard by the exam’s focus on the administrative aspects of managing GitHub Copilot. The exam tests your knowledge on topics that developers typically don’t encounter in their daily coding workflows.

Exam Structure

The exam is structured around seven key domains, each weighted differently:

1. Responsible AI (7%): This domain explores the ethical implications of AI-powered coding, including potential biases in AI models and responsible use limitations.
2. GitHub Copilot Plans and Features (31%): This domain, representing a significant portion of the exam, focuses on differentiating between Copilot Individual, Business, and Enterprise plans, understanding billing mechanisms, and demonstrating knowledge of organization-wide policy management. Key topics include data exclusion policies, audit log interpretation, and managing subscriptions.
3. How GitHub Copilot Works and Handles Data (15%): This domain tests your understanding of Copilot’s inner workings, such as how it processes data, builds context from codebases, and generates code suggestions.
4. Prompt Crafting and Prompt Engineering (9%): This domain assesses your ability to write clear, concise, and effective prompts to guide Copilot. Be prepared to answer questions about prompt engineering principles and techniques, including zero-shot and few-shot prompting.
5. Developer Use Cases for AI (14%): This domain examines your knowledge of practical Copilot applications in a developer’s daily workflow. Expect scenarios where you need to identify appropriate Copilot features for specific coding tasks.
6. Testing with GitHub Copilot (9%): This domain assesses your knowledge of using Copilot for generating unit tests, integration tests, and edge-case tests.
7. Privacy Fundamentals and Context Exclusions (15%): This domain focuses on data privacy while using Copilot. Expect questions about configuring content exclusions, understanding their effects and limitations, and knowing the ownership of generated code.

Preparation is Key

Based on my experience with the Beta exam, a strong foundation in general programming concepts and experience with Copilot itself will be very helpful. I found GitHub documentation and exploring relevant Microsoft Learn and LinkedIn Learning pathways the most beneficial.

Concentrate on grasping the intricacies of Copilot’s features, particularly those related to responsible AI usage and data handling. Additionally, hone your prompt engineering skills, as the ability to communicate effectively with Copilot is essential for maximizing its capabilities.

Remember, this guide reflects my understanding of the exam based on the Beta version and information from various GitHub documentation. I encourage you to refer to official GitHub resources and announcements for the most up-to-date information on the exam. Good luck with your preparation and the exam!

GitHub Documentation:

This should be your primary resource. Read all the documentation at least once. Key areas to focus include

• GitHub Copilot Plans and Features: This is the most heavily weighted domain on the exam. You should be very familiar with the different Copilot plans (Individual, Business, and Enterprise), the features of each plan, billing and subscription details, how organizations manage Copilot, data exclusion policies and configurations, and how to understand audit logs.
• Privacy Fundamentals and Context Exclusions: This domain focuses on the responsible use of AI. You should understand how to configure content exclusions to prevent code leaks, their mechanics, limitations, and the concept of code ownership with AI-generated code.
• How GitHub Copilot Works and Handles Data: This domain explores how Copilot processes data, understands codebases, and generates code suggestions. It would be beneficial to review documentation on code suggestion generation, prompt engineering, and data usage policies. Understand the importance of indexing repositories to improve Copilot chat’s responses.
• Prompt Crafting and Prompt Engineering: This domain emphasizes effective communication with Copilot. You should understand prompt engineering techniques like “zero-shot” and “few-shot” prompting, how to craft precise instructions, and avoid ambiguity.
• Developer Use Cases for AI: You should know the practical applications of Copilot, such as code generation, testing, bug fixing, code explanation, and regular expression creation.
• Testing with GitHub Copilot: This domain covers using Copilot for automating testing, including generating unit tests, integration tests, and edge-case tests.
• Responsible AI: This domain explores the ethical considerations of AI in coding. You should be aware of potential bias in AI models, understand AI limitations, and recognize the importance of human oversight.

Microsoft Learn:

Microsoft Learn offers a learning path specifically designed for exam preparation, covering topics like using GitHub Copilot tools to generate documentation and develop code features .

LinkedIn Learning

While still under development, LinkedIn Learning’s “Prepare for the GitHub Copilot Certification” learning path promises a video-based learning experience .

Hands-on Practice

Nothing beats practical experience. Familiarize yourself with:

• Prompt Engineering: Practice writing effective prompts to guide Copilot’s suggestions.
• Feature Exploration: Utilize Copilot in various scenarios like generating code, writing tests, and debugging.
• Policy Configuration: Gain hands-on experience with content exclusions, managing policies, and understanding their impact.

Focus on Application The exam emphasizes real-world application, particularly in the “Developer Use Cases for AI” domain . Instead of rote memorization, understand how different Copilot features and concepts apply to actual development scenarios.

Master Prompt Engineering Your ability to write effective prompts will significantly impact your Copilot experience and exam performance . Experiment with different techniques and best practices to guide Copilot accurately and efficiently.

Stay Updated The tech world constantly evolves, and so does GitHub Copilot. Regularly check for updates or changes in the exam syllabus or recommended learning materials .

References

• GitHub Copilot Documentation
• Microsoft Learn. Accelerate app development by using GitHub Copilot