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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub (Microsoft)
Exam Name:GitHub Copilot Certification Exam
Exam Number:GH-300
Available Languages:Korean, Japanese, English, Spanish, Portuguese (Brazil)
Exam Price:$99 USD
Related Certifications:GitHub Advanced Security Certification
Certificate Validity Period:24 months
Real Exam Qty:Approximately 60 scored questions + unscored items
Passing Score:Not officially disclosed (commonly reported ~700/1000)
Exam Duration:100 minutes
Exam Format:Multiple-choice, Proctored (Pearson VUE), Scenario-based
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
  • 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 2
  • 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 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.
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 (Q71-Q76):

NEW QUESTION # 71
How does GitHub Copilot Chat ensure that a function works correctly?

Answer: A

Explanation:
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.


NEW QUESTION # 72
What are the effects of content exclusions? (Each correct answer presents part of the solution. Choose two.)

Answer: A,D

Explanation:
Content exclusions prevent GitHub Copilot from using the excluded content as context and stop suggestions from being generated in those files.


NEW QUESTION # 73
You are configuring GitHub Copilot in the CLI for a smoother developer experience. Which of the following aliases can be set up to perform common actions like code suggestions and explanations?

Answer: B,C

Explanation:
ghcs is a commonly configured alias for the GitHub Copilot CLI command to suggest code. It simplifies the user experience by allowing developers to quickly prompt Copilot from the terminal.
ghce stands for GitHub Copilot Explain and is another helpful alias that allows developers to request natural language explanations for code from the terminal.
Reference:
https://docs.github.com/en/Copilot/managing-Copilot/configure-personal-settings/configuring-github-Copilot-in-the-cli#setting-up-aliases


NEW QUESTION # 74
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 # 75
What is the primary role of the /optimize slash command in Visual Studio?

Answer: D

Explanation:
The /optimize slash command in Visual Studio enhances the performance of the selected code by analyzing its runtime complexity and suggesting improvements.


NEW QUESTION # 76
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