Prepare for the GitHub Copilot Certification Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the GitHub-Copilot exam and achieve success.
How is GitHub Copilot Individual billed? (Each correct answer presents part of the solution. Choose two.)
GitHub Copilot Individual is billed as a monthly or annual subscription.
What is the correct way to access the audit log events for GitHub Copilot Business?
Audit log events for GitHub Copilot Business can be accessed through the Audit log section within the organization's GitHub settings. This log provides a record of activities related to Copilot usage and configuration.
Why is code reviewing still necessary when using GitHub Copilot to write tests?
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.
What is a benefit of using custom models in GitHub Copilot?
Custom models in GitHub Copilot allow the tool to learn from the specific code patterns and practices within your repositories. This results in suggestions that are more aligned with your organization's coding standards and conventions, improving the relevance and accuracy of the generated code.
Which of the following is a risk associated with using AI?
A risk associated with AI is that its decisions can be difficult to interpret, leading to a lack of transparency and potential misunderstandings.
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