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| Section | Weight | Objectives |
|---|
| Topic 1: Configure Privacy, Exclusions, Safeguards | 10-15% | - Agent permissions, content exclusions, org policies
|
| Topic 2: GitHub Copilot Features | 25-30% | - Multi-model, Agent Mode, Mission Control, BYOK
|
| Topic 3: Responsible AI | 15-20% | - Ethics, validation, bias mitigation, transparency
|
| Topic 4: Improve Developer Productivity | 10-15% | - Agent workflows, productivity, SDLC integration
|
| Topic 5: Apply Prompt Engineering and Context | 10-15% | - Model-specific prompting, context files, best practices
|
| Topic 6: Understand GitHub Copilot Data and Architecture | 10-15% | - Pipeline, MCP, context gathering, data handling
|
>> GitHub GitHub-Copilot Authorized Exam Dumps <<
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GitHub CopilotCertification Exam Sample Questions (Q92-Q97):
NEW QUESTION # 92
What is used by GitHub Copilot in the IDE to determine the prompt context?
- A. The open tabs in the IDE and the current folder of the terminal.
- B. All the code visible in the current IDE.
- C. Information from the IDE like open tabs, cursor location, selected code.
- D. All the code in the current repository and any git submodules.
Answer: C
Explanation:
Copilot gathers context directly from your IDE - including which files or tabs are open, where your cursor is positioned, and any selected code - to tailor its suggestions to exactly where and how you're coding.
NEW QUESTION # 93
What method can be used to interact with GitHub Copilot?
- A. From a web browser at https://github.copilot.com
- B. By using chat capabilities in NeoVim
- C. From a watch window in an IDE debug session
- D. By using a properly configured GitHub CLI
Answer: B
Explanation:
GitHub Copilot is an AI-powered code completion tool that integrates directly into supported Integrated Development Environments (IDEs) and code editors, such as Visual Studio Code, JetBrains IDEs, NeoVim, and others. Developers interact with it through their coding environment, where it provides real-time code suggestions, autocompletions, and (in some cases) chat-like capabilities via extensions or plugins (e.g., GitHub Copilot Chat in supported editors).
Evaluation of Options:
* A. By using a properly configured GitHub CLIThe GitHub CLI (Command Line Interface) is a tool for interacting with GitHub repositories and workflows from the terminal, but it is not a method for interacting with GitHub Copilot. Copilot operates within code editors/IDEs, not through the CLI.
Incorrect.
* B. By using chat capabilities in NeoVimThis is partially correct. GitHub Copilot can be used in NeoVim with the appropriate plugin (e.g., the Copilot.vim plugin), and GitHub Copilot Chat-a feature that allowsconversational interaction-may also be available depending on the setup and version.
However, "chat capabilities in NeoVim" alone is not the primary or standard way to describe Copilot interaction, as it's more about code suggestions than chat. This is the closest option but not perfectly precise.Partially correct.
* C. From a watch window in an IDE debug sessionThe "watch window" in an IDE is used during debugging to monitor variable values, not to interact with GitHub Copilot. Copilot provides suggestions while coding, not specifically in debug sessions or watch windows.Incorrect.
* D. From a web browser athttps://github.copilot.comThere is no such URL as "https://github.copilot.
com" dedicated to interacting with GitHub Copilot. Copilot is accessed via GitHub's authentication and integrated into editors/IDEs, not through a standalone web browser interface. Information about Copilot is available on GitHub's official site (e.g.,https://github.com/features/copilot), but interaction happens in the coding environment.Incorrect.
NEW QUESTION # 94
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)
- A. Provide specific success criteria
- B. Provide links to supporting documentation
- C. Provide insight on where to get the content from to get a response
- D. Provide all information about the utilized files
Answer: A,B
Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.
NEW QUESTION # 95
What can be done during AI development to minimize bias?
- A. Focus on accuracy of the data.
- B. Collect massive amounts of data for training.
- C. Improve on the computational efficiency and speed.
- D. Use diverse data, fairness metrics, and human oversight.
Answer: D
Explanation:
Incorporating diverse datasets, applying fairness metrics throughout development, and maintaining human oversight are proven strategies for detecting and mitigating bias in AI systems.
NEW QUESTION # 96
What is one of the recommended practices when using GitHub Copilot Chat to enhance code quality?
- A. Regularly review and refactor the code suggested by Copilot.
- B. Avoid using Copilot for complex tasks.
- C. Disable Copilot's inline suggestions.
- D. Rely solely on Copilot's suggestions without reviewing them.
Answer: A
Explanation:
Regularly reviewing and refactoring Copilot's output helps ensure that generated code adheres to your project's quality standards and catches any issues early.
NEW QUESTION # 97
......
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