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100% GitHub GitHub-Copilot Guaranteed Success With Testing Engine

Exam Code: GitHub-Copilot

Exam Name: GitHub CopilotCertification Exam

Updated: Nov 03, 2026

Number: 133 Q&As with Testing Engine

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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
  • 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.

Reference: https://examregistration.github.com/certification/COPILOT

GitHub GitHub-Copilot Exam Overview:

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

GitHub CopilotCertification Sample Questions:

Question #1
What caution should developers exercise when using GitHub Copilot for assistance with mathematical computations?

A. GitHub Copilot's reliance on pattern-based responses without verifying computation accuracy.
B. GitHub Copilot's automatic update of outdated mathematical formulas to modern standards.
C. GitHub Copilot's ability to execute and verify mathematical results in real-time.
D. GitHub Copilot's capability to optimize complex mathematical algorithms beyond manual coding.


Question #2
What configuration needs to be set to get help from Microsoft and GitHub protecting against IP infringement while using GitHub Copilot?

A. Enforce blocking of MIT or GPL licensed code
B. You need to check code suggestions yourself before accepting
C. Suggestions matching public code to 'blocked'
D. Enable GitHub Copilot license checking


Question #3
What are the additional checks that need to pass before the GitHub Copilot responses are submitted to the user? Each correct answer presents part of the solution. (Choose two.)

A. Code quality
B. Compatibility with user-specific settings
C. Suggestions matching public code (optional based on settings)
D. Performance benchmarking


Question #4
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?

A. By using specific prompt examples in your chat request.
B. By using a specific slash command in the prompt.
C. By using a specific setting in GitHub Copilot's configuration.
D. By using a specific command in the terminal.


Question #5
Which Copilot Individual features are available when using a supported extension for Visual Studio, VS Code, or JetBrains IDEs? (Each correct answer presents part of the solution. Choose two.)

A. Knowledge Base
B. Chat
C. Pull Request Diff Analysis
D. Code suggestions


Solutions:

Question #1
Correct Answer: A
Question #2
Correct Answer: C
Question #3
Correct Answer: A,C
Question #4
Correct Answer: A
Question #5
Correct Answer: B,D

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