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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.

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GitHub CopilotCertification Exam Sample Questions (Q112-Q117):

NEW QUESTION # 112
How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

Answer: C,D

Explanation:
GitHub Copilot Enterprise assists in code reviews by generating summaries of pull requests and answering questions about the changes made.


NEW QUESTION # 113
Your company recently adopted GitHub Copilot Business, and leadership wants to ensure accountability and transparency in its usage. Which of the following best describes the purpose of audit logs in GitHub Copilot Business?

Answer: B

Explanation:
Organization audit logs are primarily used to track administrative actions such as enabling or disabling GitHub Copilot, identifying the user who performed the action, and the timestamp. This promotes accountability, transparency, and security compliance.
Reference:
https://docs.github.com/en/Copilot/managing-Copilot/managing-github-Copilot-in-your-organization/reviewing-activity-related-to-github-Copilot-in-your-organization/reviewing-audit-logs- for-Copilot-business


NEW QUESTION # 114
Which of the following is the correct way to access the audit log events for GitHub Copilot Business?

Answer: B

Explanation:
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.


NEW QUESTION # 115
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 # 116
Which Microsoft ethical AI principle is aimed at ensuring AI systems treat all people equally?

Answer: C

Explanation:
The principle of fairness ensures that AI systems treat all people equally and avoid discriminatory outcomes.


NEW QUESTION # 117
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