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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
Topic 2
  • Privacy Fundamentals and Context Exclusions: This domain focuses on Security Engineers and Compliance Officers and addresses improving code quality with Copilotโ€™s test suggestions and security optimizations. It covers identification of security vulnerabilities, performance enhancements, and privacy features like content exclusions at repository and organization levels with explanation of their limitations. Candidates learn about safeguarding mechanisms such as duplication detection, contractual protections, security checks, and troubleshooting guide for common Copilot issues including context exclusions and suggestion gaps.
Topic 3
  • Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilotโ€™s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilotโ€™s impact is also included.
Topic 4
  • Responsible :This section of the exam measures skills of AI Ethics Officers and Risk Managers and covers the responsible and ethical usage of AI technologies. It explains the risks and limitations associated with generative AI tools, including biases in training data and the need to validate AI outputs. Candidates learn how to operate AI responsibly by identifying potential harms such as bias, fairness, privacy concerns, and mitigating these harms by applying ethical AI principles.

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Microsoft GitHub Copilot Sample Questions (Q98-Q103):

NEW QUESTION # 98
How can GitHub Copilot assist in maintaining consistency across your tests?

Answer: A

Explanation:
"Copilot learns from the patterns in your existing tests and suggests similar structures, which helps maintain consistency across the test suite." This confirms that Copilot supports test consistency through pattern recognition and suggestion.
References: GitHub Copilot testing documentation.


NEW QUESTION # 99
Why is it important to ensure the security of the code used in Generative AI (Gen AI) tools?

Answer: D

Explanation:
"Securing the code used with generative AI prevents unauthorized access, helps safeguard sensitive data, and protects against potential breaches." This confirms option A is correct because the primary importance lies in avoiding unauthorized access and breaches.
References: GitHub Copilot responsible use and AI security documentation.


NEW QUESTION # 100
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

Answer: A

Explanation:
The best way to share feedback on GitHub Mobile is using the emojis in the Copilot Chat interface, which allows for direct and immediate feedback.
Reference: GitHub Copilot Mobile documentation.


NEW QUESTION # 101
When using GitHub Copilot Chat to generate unit tests, which slash command would you use?

Answer: B


NEW QUESTION # 102
Why is code reviewing still necessary when using GitHub Copilot to write tests?

Answer: B

Explanation:
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.


NEW QUESTION # 103
......

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