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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:Approximately 60 scored questions + unscored items
Passing Score:Not officially disclosed (commonly reported ~700/1000)
Exam Duration:100 minutes
Exam Price:$99 USD
Related Certifications:GitHub Advanced Security Certification
Available Languages:Spanish, English, Japanese, Portuguese (Brazil), Korean
Exam Format:Proctored (Pearson VUE), Multiple-choice, Scenario-based
Certificate Validity Period:24 months
Recommended Training:GitHub Copilot Learning Path (Microsoft Learn)
GitHub Docs Copilot Guide
Exam Registration:Official GitHub Copilot Certification Page
Microsoft Learn Certifications
Sample Questions:GitHub GitHub-Copilot Sample Questions
Exam Way:Online proctored or Pearson VUE test center
Pre Condition:No formal prerequisites required; recommended familiarity with GitHub and basic programming experience
Official Syllabus URL:https://learn.github.com/certification/COPILOT

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • How GitHub Copilot Works and Handles Data: This section of the exam measures the skills of Data Security Specialists and DevOps Engineers and covers how GitHub Copilot processes data, handles code suggestions and manages privacy concerns. It explains the data pipeline for Copilot’s suggestions, how it gathers context, and how prompts are processed through its AI model. The section also discusses the limitations of AI-generated code, the effects of historical data on suggestions, and the role of prompt crafting. Best practices for improving prompt effectiveness and optimizing AI-generated responses are included.
Topic 3
  • 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.
Topic 4
  • 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 5
  • 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.

GitHub CopilotCertification Exam Sample Questions (Q36-Q41):

NEW QUESTION # 36
What GitHub Copilot configuration needs to be enabled to protect against IP infringements?

Answer: C

Explanation:
Enabling the Block suggestions matching public code setting turns on Copilot's duplication‑ detection filter, which checks generated snippets against public repositories and suppresses any match, helping prevent inadvertent IP infringement.


NEW QUESTION # 37
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 # 38
How do you generate code suggestions with GitHub Copilot in the CLI?

Answer: D

Explanation:
In the CLI, GitHub Copilot generates code suggestions by analyzing code comments. You write comments describing what you want, and Copilot provides relevant code suggestions. You then select the best suggestion from the list.


NEW QUESTION # 39
A large enterprise wants to enhance the code assistance support for their developers by incorporating internal code standards and best practices into GitHub Copilot. The IT team is also looking for scalable AI assistance with enterprise-level data management and governance. Which of the following plans can best accommodate this requirement?

Answer: C

Explanation:
GitHub Copilot Enterprise includes support for private Knowledge Bases, which enables integration of internal documentation, best practices, and custom code snippets. It also supports enterprise-grade governance, security, and policy enforcement features-ideal for large organizations.
Reference:
https://learn.microsoft.com/en-us/training/modules/github-Copilot-management-and-customizations/2-explore-github-Copilot-plans-associated-management-customization- features?ns-enrollment-type=learningpath&ns-enrollment-id=learn.github-Copilot


NEW QUESTION # 40
GitHub Copilot in the Command Line Interface (CLI) can be used to configure the following settings: (Each correct answer presents part of the solution. Choose two.)

Answer: A,B

Explanation:
GitHub Copilot in the CLI allows configuration of settings such as the default execution confirmation and usage analytics. These settings help tailor the CLI experience to the user's preferences.


NEW QUESTION # 41
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