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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub (Microsoft)
Exam Name:GitHub Copilot Certification Exam
Exam Number:GH-300
Exam Format:Proctored (Pearson VUE), Multiple-choice, Scenario-based
Real Exam Qty:Approximately 60 scored questions + unscored items
Certificate Validity Period:24 months
Related Certifications:GitHub Advanced Security Certification
Exam Duration:100 minutes
Exam Price:$99 USD
Available Languages:Spanish, Portuguese (Brazil), Korean, English, Japanese
Passing Score:Not officially disclosed (commonly reported ~700/1000)
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
  • 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.

GitHub CopilotCertification Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
When using GitHub Copilot Chat to generate boilerplate code for various test types, how can you guide the AI to follow the testing standards of your company?

Answer: D

Explanation:
Providing concrete examples of your company's test structure and standards within the prompt steers Copilot Chat to generate boilerplate that aligns with your guidelines.


NEW QUESTION # 21
What reasons could apply if code suggestions are not working in your editor? (Choose three.)

Answer: C,D,E

Explanation:
Without an active internet connection, Copilot cannot reach its service to fetch suggestions.
If you're editing in a language that Copilot doesn't support, it won't produce completions.
An invalid or expired Copilot license will prevent any suggestions from appearing.


NEW QUESTION # 22
What types of content can GitHub Copilot Knowledge Base answer questions about? Each correct answer presents part of the solution. (Choose three.)

Answer: A,D,E

Explanation:
Code snippets: The Knowledge Base ingests and indexes your repository's source code so Copilot can answer questions about specific code examples.
Design patterns: It can surface relevant architectural and design best practices drawn from your team's patterns.
Documentation: It incorporates your project's README, wikis, and other docs to provide contextual answers.


NEW QUESTION # 23
What is zero-shot prompting?

Answer: B

Explanation:
Zero-shot prompting involves asking GitHub Copilot a question or giving a task without providing any examples. This relies on the model's pre-existing knowledge to generate a response.


NEW QUESTION # 24
A developer is working for an enterprise that hosts all its code on Bitbucket and wants to leverage GitHub Copilot. However, their organization doesn't have any GitHub repositories. Can they still access GitHub Copilot?

Answer: D

Explanation:
GitHub Copilot Business supports usage with non-GitHub repositories. Developers can use Copilot in supported IDEs regardless of the repository hosting platform, enabling access to AI coding suggestions even if code is hosted outside GitHub.
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 # 25
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