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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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.

GitHub CopilotCertification Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
What is the correct way to exclude specific files from being used by GitHub Copilot Business during code suggestions?

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

Answer: B

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 # 25
What method can be used to interact with GitHub Copilot?

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

Answer: C

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 # 26
Which of the following statements best describes the impact of GitHub Copilot on the software development process?

A. It increases productivity by automating repetitive coding tasks.
B. It decreases software vulnerabilities from third party dependencies.
C. It replaces the need for developers in the software development process.
D. It reduces overhead by automating testing workflows.

Answer: A

Explanation:
GitHub Copilot primarily impacts the software development process by increasing productivity through automating repetitive coding tasks.

NEW QUESTION # 27
Which GitHub Copilot plan allows for prompt and suggestion collection?

A. GitHub Copilot Codespace
B. GitHub Copilot Enterprise
C. GitHub Copilot Business
D. GitHub Copilot Individuals

Answer: B

Explanation:
GitHub Copilot Enterprise allows for prompt and suggestion collection, enabling organizations to analyze and improve their usage of the tool.

NEW QUESTION # 28
What is a benefit of using custom models in GitHub Copilot?

A. Responses are guaranteed to be correct
B. Responses are faster to produce and appear sooner
C. Responses use the organization's LLM engine
D. Responses use practices and patterns in your repositories

Answer: D

Explanation:
Custom models in GitHub Copilot allow the tool to learn from the specific code patterns and practices within your repositories. This results in suggestions that are more aligned with your organization's coding standards and conventions, improving the relevance and accuracy of the generated code.

NEW QUESTION # 29
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