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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub (Microsoft)
Exam Name:GitHub Copilot Certification Exam
Exam Number:GH-300
Certificate Validity Period:24 months
Passing Score:Not officially disclosed (commonly reported ~700/1000)
Related Certifications:GitHub Advanced Security Certification
Exam Price:$99 USD
Exam Duration:100 minutes
Exam Format:Multiple-choice, Scenario-based, Proctored (Pearson VUE)
Available Languages:English, Spanish, Korean, Japanese, Portuguese (Brazil)
Real Exam Qty:Approximately 60 scored questions + unscored items
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
  • 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 2
  • 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 3
  • 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 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.

GitHub CopilotCertification Exam Sample Questions (Q14-Q19):

NEW QUESTION # 14
When using GitHub Copilot to identify missing tests in your codebase, which of the following is the most important factor to consider?

Answer: A

Explanation:
GitHub Copilot needs the relevant code and test files in its context window to spot where tests are missing - without that context, it can't accurately identify gaps.


NEW QUESTION # 15
Select a strategy to increase the performance of GitHub Copilot Chat.

Answer: B

Explanation:
Applying prompt engineering techniques to be more specific is the best strategy to increase the performance and relevance of GitHub Copilot Chat's responses.


NEW QUESTION # 16
Your organization wants GitHub Copilot Enterprise to suggest code based on internal coding practices and documentation. Which of the following features should be configured to allow Copilot to access and utilize organization-specific content?

Answer: B

Explanation:
GitHub Copilot Enterprise allows organizations to create and configure Knowledge Bases containing internal code snippets, documentation, best practices, and more. These resources are used by Copilot to provide contextually relevant suggestions based on proprietary content.
Reference:
https://docs.github.com/en/enterprise-cloud@latest/Copilot/customizing-Copilot/managing-Copilot-knowledge-bases


NEW QUESTION # 17
How does GitHub Copilot assist developers in minimizing context switching?

Answer: D

Explanation:
By surfacing code suggestions and documentation directly in your editor, Copilot keeps you working within your IDE and reduces the need to switch to external resources.


NEW QUESTION # 18
What are the potential limitations of GitHub Copilot in maintaining existing codebases?

Answer: A

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 # 19
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