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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • Responsible AI: This section of the exam measures the skills of AI Ethics Analysts and AI Developers and covers the principles of responsible AI usage, the risks associated with AI, and the limitations of generative AI tools. It includes the importance of validating AI-generated outputs and operating AI systems responsibly. It also explores potential harms such as bias, privacy concerns, and fairness issues, along with methods to mitigate these risks. The ethical considerations of AI development and deployment are also discussed.
Topic 3
  • 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.

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GitHub CopilotCertification Exam Sample Questions (Q71-Q76):

NEW QUESTION # 71
Which of the following are true about code suggestions? Each correct answer presents part of the solution. (Choose two.)

Answer: A,C

Explanation:
You can use keyboard shortcuts (e.g., Tab or Ctrl+→) to accept the next word (or token) of an inline suggestion.
When you request alternative completions, Copilot opens them in the Copilot pane (a new editor tab) where you can browse and insert the option you prefer.


NEW QUESTION # 72
In what ways can GitHub Copilot support a developer during the code refactoring process? Each correct answer presents part of the solution. (Choose two.)

Answer: A,C

Explanation:
Copilot analyzes your code and suggests refactorings that improve readability and maintainability by applying established best practices.
It can propose alternative code patterns that reduce complexity and boost performance through targeted transformations.


NEW QUESTION # 73
What method can a developer use to generate sample data with GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

Answer: B,D

Explanation:
GitHub Copilot can generate sample data by creating fictitious information based on patterns in its training data and by using suggestions based on API documentation within the repository.


NEW QUESTION # 74
What GitHub Copilot configuration needs to be enabled to protect against IP infringements?

Answer: D

Explanation:
Enabling the Block suggestions matching public code setting turns on Copilot's duplication‑ detection filter, which checks generated snippets against public repositories and suppresses any match, helping prevent inadvertent IP infringement.


NEW QUESTION # 75
Which GitHub Copilot plan could an Azure DevOps organization use without requiring a GitHub Enterprise license?

Answer: B

Explanation:
The GitHub Copilot Business plan (branded for use with Azure DevOps) works on any DevOps platform - including Azure DevOps - without needing a GitHub Enterprise Cloud subscription. This lets organizations use Copilot's AI assistance in their existing Azure DevOps workflows without purchasing a GitHub Enterprise license.


NEW QUESTION # 76
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