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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub
Exam Name:Microsoft GitHub Copilot
Exam Number:GH-300
Related Certifications:GitHub Copilot Certified Professional
Available Languages:English
Passing Score:700 / 1000
Exam Duration:100 minutes
Exam Format:Multiple Choice
Real Exam Qty:60-65
Certificate Validity Period:2 years
Exam Price:$99 USD
Sample Questions:GitHub GitHub-Copilot Sample Questions
Exam Way:Proctored (Online or Offline Test Centers)
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-copilot

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 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
  • 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.

GitHub CopilotCertification Exam Sample Questions (Q47-Q52):

NEW QUESTION # 47
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: B

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 # 48
What method can a developer use to generate sample data with GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

Answer: B,C

Explanation:
GitHub Copilot can generate sample data by creating fictitious information based on patterns in its training data and by using suggestions based on API documentation within the repository.


NEW QUESTION # 49
How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

Answer: B,C

Explanation:
GitHub Copilot Enterprise assists in code reviews by generating summaries of pull requests and answering questions about the changes made.


NEW QUESTION # 50
What are the potential limitations of GitHub Copilot in maintaining existing codebases?

Answer: D

Explanation:
GitHub Copilot operates within a limited context window and may not capture all dependencies or the full project structure in a large codebase, so it can misunderstand context and require developer oversight.


NEW QUESTION # 51
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: A

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 # 52
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