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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
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	GitHub Copilot Plans and FeaturesThis section of the exam measures the skills of Software Engineers and IT Administrators and covers different GitHub Copilot plans, including Individual, Business, and Enterprise editions. It explains the integration of GitHub Copilot within IDEs and discusses key features such as inline chat, multiple suggestions, and exception handling. The section details the policies for managing GitHub Copilot within organizations, including auditing logs and API management. It also highlights advanced functionalities like knowledge bases for improved code quality and best practices for Copilot Chat usage.
Topic 4	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 5	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.

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GitHub CopilotCertification Exam Sample Questions (Q10-Q15):

NEW QUESTION # 10
How can you get multiple suggestions from GitHub Copilot?

A. By asking for multiple suggestions using comments in your code
B. By using @workspace in the chat window
C. By using the inline chat functionality with the command 'multiple'
D. By opening the completions panel in your editor

Answer: D

Explanation:
You can get multiple suggestions by opening the completions panel in your editor, which displays alternative code suggestions.

NEW QUESTION # 11
What method can be used to interact with GitHub Copilot?

A. By using chat capabilities in NeoVim
B. By using a properly configured GitHub CLI
C. From a web browser at https://github.copilot.com
D. From a watch window in an IDE debug session

Answer: A

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 # 12
How can you improve the context used by GitHub Copilot? (Each correct answer presents part of the solution.
Choose two.)

A. By adding the full file paths to your prompt of important files
B. By opening the relevant tabs in your IDE
C. By adding relevant code snippets to your prompt
D. By adding the important files to your .gitconfig

Answer: B,C

Explanation:
Improving the context for GitHub Copilot involves opening relevant files in your IDE to provide immediate context and adding relevant code snippets directly to your prompts to give Copilot specific examples and information.

NEW QUESTION # 13
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)

A. Provide specific success criteria
B. Provide all information about the utilized files
C. Provide insight on where to get the content from to get a response
D. Provide links to supporting documentation

Answer: A,D

Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.

NEW QUESTION # 14
What is the correct way to exclude specific files from being used by GitHub Copilot Business during code suggestions?

A. Use the GitHub Copilot settings in the user interface to exclude files.
B. Add the specific files to a copilot.ignore file.
C. Rename the files to include the suffix _no_copilot.
D. Modify the .gitignore file to include the specific files.

Answer: A

Explanation:
The correct way to exclude files is through the GitHub Copilot settings in the user interface, which allows administrators to specify files and directories to be ignored.

NEW QUESTION # 15
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GitHub GitHub-Copilot Exam Syllabus Topics:

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GitHub CopilotCertification Exam Sample Questions (Q10-Q15):

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