Prepare for the GitHub Copilot GH-300 certification with a comprehensive practice exam designed to assess your knowledge and strengthen your skills. Test your understanding of GitHub Copilot features, prompt engineering, responsible AI, code generation and improvement, as well as security and privacy best practices. Practice with multiple-choice questions covering the key knowledge areas assessed in the official certification exam.
Prepare for the GitHub Copilot GH-300 certification with a comprehensive practice exam designed to assess your knowledge and strengthen your skills. Test your understanding of GitHub Copilot features, prompt engineering, responsible AI, code generation and improvement, as well as security and privacy best practices. Practice with multiple-choice questions covering the key knowledge areas assessed in the official certification exam.
Use this exam to assess your knowledge. Take time to read each question before answering.
Understand responsible AI principles, identify the risks and limitations of generative AI, evaluate the reliability of AI-generated suggestions, and apply best practices for validation, transparency, and ethical use of generated code.
Master GitHub Copilot in development environments, including inline code suggestions, Copilot Chat, Copilot CLI, Agent Mode, Copilot Edits, and Model Context Protocol (MCP). Use code review, custom instructions, context spaces, and organization-wide administration settings.
Understand how GitHub Copilot works, including data processing and flow, prompt construction, request filtering, and the lifecycle of code suggestions. Identify the capabilities and limitations of large language models (LLMs).
Design clear, precise, and effective prompts for GitHub Copilot. Understand prompt structure, context selection, zero-shot and few-shot prompting techniques, and the use of conversation history to improve the relevance of generated responses.
Use GitHub Copilot to generate, explain, refactor, and document code. Accelerate development, modernize legacy applications, create sample data, generate unit and integration tests, identify edge cases, and improve performance and security.
Configure GitHub Copilot privacy settings and content exclusions. Understand generated code ownership considerations, manage filtering of suggestions matching public code, and troubleshoot issues related to safeguards and content exclusions.
Which of the following is NOT a selectable mode in GitHub Copilot Chat?
What are smart actions?
Which option below is NOT a possible way to grant access to Copilot for members of an organization?
Which of the following describes the GitHub Copilot Editor configuration file?
What are the post-processing checks performed on GitHub Copilot's responses?
Which statement correctly describes GitHub Copilot CLI?
Which of the following is a potential benefit of using GitHub Copilot to enhance developer workflows?
Which of the following options best describes GitHub Copilot?
What does GitHub Copilot analyze to offer relevant suggestions as you are developing new code?
Which of the following integrates GitHub Copilot Chat with external tools?
Which elements can GitHub Copilot use as context when generating suggestions?
Which IDEs are not supported by GitHub Copilot?
What is an alias used for when using GitHub Copilot?
Which GitHub Copilot subscription plans support organization-level custom instructions?
Which set of principles correctly represents Microsoft's six key principles for Responsible AI that guide GitHub Copilot's development?
What happens when you exclude content from GitHub Copilot?
Which steps occur when GitHub Copilot's proxy service processes a prompt?
Where can you find information about concerns related to security, intellectual property and privacy regarding the usage of GitHub Copilot?
Can GitHub Copilot use semantic information from a file that is ignored by GitHub Copilot content exclusions?
How can you provide GitHub Copilot with context to generate tailored responses for your repository?
What are some of the principles of Prompt Engineering?
How does GitHub Copilot's matching public code feature work?
You are developing an application in Kotlin. What do you have to keep in mind when using GitHub Copilot?
Which of the sentences is correct?
Which of the following describes how to use the GitHub Copilot's Productivity API?
Which statements are correct regarding the usage of @workspace and #codebase?
Which statements are true about GitHub Copilot content exclusions?
Which is true about Copilot's Content exclusions?
When adding context in the chat, it is possible to add single files, but not entire folders. This statement is:
How can you exclude specific files from GitHub Copilot?
Which of the following can be added as context for your prompt in GitHub Copilot Chat?
How is seat usage calculated for GitHub Copilot at the enterprise level during a billing cycle?
Which statements are correct about GitHub Copilot CLI?
Which features are available in GitHub Copilot and GitHub Copilot Chat?
Quelle commande permet d'installer GitHub Copilot CLI ?
How does GitHub Copilot handle data retention for code suggestions in the IDE?
Is GitHub Copilot free to use for everyone?
What is the primary purpose of the '/tests' slash command in GitHub Copilot?
What is the easiest way to get started with GitHub Copilot?
Which Microsoft ethical AI principle is aimed at ensuring AI systems treat all people equally?
What can be done during AI development to minimize bias?
Why is it important to ensure the security of the code used in Generative AI (Gen AI) tools?
How can the concept of fairness be integrated into the process of operating an AI tool?
What types of prompts or code snippets might be flagged by the GitHub Copilot toxicity filter? Each correct answer presents part of the solution. (Choose two.)
Which of the following is a risk associated with using AI?
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?
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