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[General] GitHub-Copilot New Study Notes - GitHub-Copilot Valid Exam Discount

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【General】 GitHub-Copilot New Study Notes - GitHub-Copilot Valid Exam Discount

Posted at yesterday 09:47      View：1 | Replies：0        Print      Only Author   [Copy Link] 1#
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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
  • 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
  • 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
  • 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 5
  • 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 (Q67-Q72):NEW QUESTION # 67
What is a limitation of content exclusions?
  • A. Content exclusions can be worked around as it is only available for Git repositories.
  • B. Repository administrators and organization owners cannot manage content exclusion settings.
  • C. Content exclusions are only available in the GitHub Copilot Individual plan.
  • D. Content exclusions can only be configured by an enterprise administrator.
Answer: A
Explanation:
A limitation is that content exclusions are only available for Git repositories, meaning they can be worked around if content is accessed through other means.

NEW QUESTION # 68
What role does chat history play in GitHub Copilot's code suggestions?
  • A. Chat history is used to train the GitHub Copilot model in real-time.
  • B. Chat history is irrelevant to GitHub Copilot and does not affect its functionality.
  • C. Chat history is stored and shared with other users to enhance collaboration.
  • D. Chat history provides context to GitHub Copilot, improving the relevance and accuracy of its code suggestions.
Answer: D
Explanation:
Chat history provides valuable context to GitHub Copilot, helping it generate more relevant and accurate code suggestions based on previous interactions and conversations.

NEW QUESTION # 69
How can GitHub Copilot assist developers during the requirements analysis phase of the Software Development Life Cycle (SDLC)?
  • A. By identifying and fixing potential requirement conflicts when using /help.
  • B. By managing stakeholder communication and meetings.
  • C. By providing templates and code snippets that help in documenting requirements.
  • D. By automatically generating detailed requirements documents.
Answer: C
Explanation:
GitHub Copilot can assist during the requirements analysis phase by providing templates and code snippets that aid in documenting requirements. This helps streamline the process of capturing and organizing project requirements.

NEW QUESTION # 70
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)
  • A. By adding comments to your code and triggering a suggestion.
  • B. By using the "/fix" command in GitHub Copilot in-line chat.
  • C. By highlighting the code you want to fix, right-clicking, and selecting "Refactor using GitHub Copilot."
  • D. By highlighting the code you want to fix, right-clicking, and selecting "Fix using GitHub Copilot."
  • E. By running the gh copilot fix command.
Answer: A,C
Explanation:
You can use GitHub Copilot for inline refactoring suggestions by adding comments to your code to trigger suggestions and by highlighting the code and selecting "Refactor using GitHub Copilot" from the context menu.

NEW QUESTION # 71
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)
  • A. Provide all information about the utilized files
  • B. Provide insight on where to get the content from to get a response
  • C. Provide links to supporting documentation
  • D. Provide specific success criteria
Answer: C,D
Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.

NEW QUESTION # 72
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