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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:Proctored (Pearson VUE), Multiple-choice, Scenario-based
Certificate Validity Period:24 months
Available Languages:English, Korean, Japanese, Portuguese (Brazil), Spanish
Passing Score:Not officially disclosed (commonly reported ~700/1000)
Real Exam Qty:Approximately 60 scored questions + unscored items
Related Certifications:GitHub Advanced Security Certification
Exam Price:$99 USD
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
  • 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
  • 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
  • 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 (Q60-Q65):

NEW QUESTION # 60
What is one of the recommended practices when using GitHub Copilot Chat to enhance code quality?

Answer: B

Explanation:
Regularly reviewing and refactoring Copilot's output helps ensure that generated code adheres to your project's quality standards and catches any issues early.


NEW QUESTION # 61
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,D

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 # 62
Identify the steps involved in the life cycle of a GitHub Copilot code suggestion? Each correct answer presents part of the solution. (Choose two.)

Answer: C,D

Explanation:
GitHub Copilot begins by capturing your current editing context - such as surrounding code, comments, and cursor position - and then feeds that into its AI model to generate code suggestions tailored to what you're working on.


NEW QUESTION # 63
As a developer who is evaluating the efficiency of GitHub Copilot in generating accurate code across different problem domains. During your R&D, you want to consider the limitations of GenAI tools like Copilot. Which of the following options best describes a core limitation?

Answer: A

Explanation:
Copilot is trained on a vast amount of data, which is publicly available; this data may include the biased, outdated, or incorrect practices of code implementation. This typically highlights a key concern in Responsible AI.
References:
https://learn.microsoft.com/en-us/training/modules/responsible-ai-with-github-Copilot/2-manage-ai-risks


NEW QUESTION # 64
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?

Answer: C

Explanation:
The principle of transparency emphasizes that AI systems should be understandable and provide clear information about their operations. This ensures that users can understand how the AI arrivesat its decisions and suggestions.


NEW QUESTION # 65
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