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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub, Microsoft
Exam Name:GitHub Copilot Certification Exam
Exam Number:GH-300
Real Exam Qty:60–65
Available Languages:English, Spanish, Korean, Japanese, Portuguese (Brazil)
Exam Format:Multiple-choice, Scenario-based, Multi-select, Case study
Exam Price:$99 USD
Passing Score:700 / 1000 (approx. 70%)
Exam Duration:100 minutes
Certificate Validity Period:24 months
Recommended Training:GitHub Copilot Learning Path
GitHub Official Documentation
Exam Registration:Official GitHub Certification Page
Pearson VUE Registration
Sample Questions:GitHub GitHub-Copilot Sample Questions
Exam Way:Online proctored or in-person at Pearson VUE test centers
Pre Condition:No mandatory prerequisites; recommended: foundational GitHub knowledge, experience with at least one programming language, hands-on use of Copilot
Official Syllabus URL:https://learn.github.com/certification/COPILOT

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • Developer Use Cases for AI: This section of the exam measures skills of Full-Stack Developers and Cloud Engineers and covers how AI enhances developer productivity across various tasks such as learning new programming languages, debugging, writing documentation, and refactoring code. It discusses how GitHub Copilot integrates with the Software Development Lifecycle (SDLC) and its role in modernizing legacy applications. It also highlights the use of AI for personalized responses, sample data generation, and improving overall efficiency in software development.
Topic 2
  • Privacy Fundamentals and Context Exclusions: This section of the exam measures skills of Cybersecurity Specialists and Compliance Officers and covers privacy safeguards and content exclusion settings in GitHub Copilot. It explains how Copilot can identify security vulnerabilities, suggest optimizations, and enforce secure coding practices. It also includes details on content ownership, data filtering mechanisms, and exclusion configurations. The section concludes with troubleshooting guidelines for managing context exclusions and ensuring compliance with organizational security policies.
Topic 3
  • GitHub Copilot Plans and FeaturesThis section of the exam measures the skills of Software Engineers and IT Administrators and covers different GitHub Copilot plans, including Individual, Business, and Enterprise editions. It explains the integration of GitHub Copilot within IDEs and discusses key features such as inline chat, multiple suggestions, and exception handling. The section details the policies for managing GitHub Copilot within organizations, including auditing logs and API management. It also highlights advanced functionalities like knowledge bases for improved code quality and best practices for Copilot Chat usage.
Topic 4
  • Responsible AI: This section of the exam measures the skills of AI Ethics Analysts and AI Developers and covers the principles of responsible AI usage, the risks associated with AI, and the limitations of generative AI tools. It includes the importance of validating AI-generated outputs and operating AI systems responsibly. It also explores potential harms such as bias, privacy concerns, and fairness issues, along with methods to mitigate these risks. The ethical considerations of AI development and deployment are also discussed.
Topic 5
  • Testing with GitHub Copilot: This section of the exam measures skills of QA Engineers and Test Automation Specialists and covers AI-assisted testing methodologies, including the generation of unit tests, integration tests, and edge case detection. It explains how GitHub Copilot improves test effectiveness by suggesting relevant assertions and boilerplate test cases. The section also discusses privacy considerations, organizational code suggestion settings, and best practices for configuring GitHub Copilot’s testing features.
Topic 6
  • Prompt Engineering: This section of the exam measures skills of AI Engineers and Software Developers and covers the fundamentals of prompt engineering, including key principles, techniques, and best practices for generating high-quality outputs. It explains different prompting strategies such as zero-shot and few-shot prompting, how context influences AI-generated responses, and the role of structured prompts in guiding Copilot's behavior. It also discusses the prompt lifecycle and ways to enhance model performance through refined input instructions.

GitHub CopilotCertification Exam Sample Questions (Q89-Q94):

NEW QUESTION # 89
What is the correct sequence of steps to install GitHub Copilot CLI on a developer's system?

Answer: A

Explanation:
To install GitHub Copilot in the CLI, developers must first have the GitHub CLI (gh) installed.
Then, they run the correct command: gh extension install github/gh-Copilot. Authentication is completed with gh auth login. This sequence ensures the extension is installed properly and securely.
Reference:
https://docs.github.com/en/Copilot/managing-Copilot/configure-personal-settings/installing-github-Copilot-in-the-cli


NEW QUESTION # 90
How can users provide feedback about GitHub Copilot Chat using their IDE?

Answer: D

Explanation:
In supported IDEs (e.g., Visual Studio or JetBrains), you can click the "Share Feedback" (or
"Send feedback") button directly in the Copilot Chat panel to submit likes, dislikes, and comments on any response.


NEW QUESTION # 91
How does GitHub Copilot Chat help to fix security issues in your codebase?

Answer: C

Explanation:
Copilot Chat can analyze your code, highlight known vulnerability patterns, and annotate its suggestions with explanations of the security issues and proposed fixes.


NEW QUESTION # 92
You are using GitHub Copilot under an Individual plan within Visual Studio Code. Which of the following is a core feature available to you under this plan?

Answer: C

Explanation:
GitHub Copilot Individual offers context-aware suggestions directly in the IDE, helping developers by predicting and completing code based on the current file and surrounding context.
Reference:
https://learn.microsoft.com/en-us/training/modules/introduction-to-github-Copilot/2-github-Copilot-your-ai-pair-programmer


NEW QUESTION # 93
Which of the following are true about code suggestions? Each correct answer presents part of the solution. (Choose two.)

Answer: A,D

Explanation:
You can use keyboard shortcuts (e.g., Tab or Ctrl+→) to accept the next word (or token) of an inline suggestion.
When you request alternative completions, Copilot opens them in the Copilot pane (a new editor tab) where you can browse and insert the option you prefer.


NEW QUESTION # 94
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