Free Exam GH-300: GitHub Copilot Practice Questions
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Sample Practice Questions
Try these 10 sample questions from the Exam GH-300: GitHub Copilot practice bank. Each includes the answer and explanation. Continue with the interactive practice above to review the full question set.
1Which responsible AI principle addresses avoiding different impacts on similarly situated groups?
- A. Transparency
- B. Fairness
- C. Accountability
- D. Inclusiveness
Answer: B
Explanation: The module states, "AI systems should treat everyone fairly, avoiding differential impacts on similarly situated groups." This is the fairness principle; inclusiveness focuses on access and empowerment.
Reference: Microsoft and GitHub's six principles of responsible AI — Fairness: AI systems should treat all people fairly
2A developer has a GitHub account with an existing Copilot subscription. How should they begin setting up Copilot in VS Code?
- A. Open a repository owned by the subscribed account while using another sign-in
- B. Sign in to a separate personal account and expect the existing license to transfer
- C. Set the Git commit email to the subscribed account without changing the sign-in
- D. Select Use AI Features and sign in with the account holding the subscription
Answer: D
Explanation: The guide says, "Hover over the Copilot icon in the Status Bar and select Use AI Features." It also states, "If you already have a Copilot subscription for your account, VS Code will use that subscription." Copilot access follows the authenticated account, not repository ownership or commit metadata.
Reference: Set up GitHub Copilot in VS Code — Set up GitHub Copilot
3Before a Copilot Chat request reaches the language model, how is the user's prompt handled?
- A. It is sent alone, with repository and chat context discarded
- B. It is pre-processed and combined with available contextual information
- C. It is compiled into executable code regardless of the input format
- D. It is added to the model's training weights before inference
Answer: B
Explanation: The card states, "The user's prompt is pre-processed by the system, combined with contextual information (for example, the current repository, open files, or chat history), and sent to a large language model." This is runtime input construction, not retraining.
Reference: Application card: GitHub Copilot Chat — 6. Performance / Input processing
4Which prompt organization follows GitHub's guidance for stating a goal and its requirements?
- A. Give the broad goal, then specific requirements with important ones first
- B. List minor formatting preferences before mentioning the task's purpose
- C. Supply a broad goal and leave required behavior for Copilot to infer
- D. Place lower-priority details first and state the main objective at the end
Answer: A
Explanation: The guide says, "first give Copilot a broad description of the goal or scenario. Then list any specific requirements. Put your most important requirements first." This makes the goal and priorities explicit.
Reference: Prompt engineering for GitHub Copilot — Start general, then get specific
5Which request asks Copilot to refactor an existing implementation?
- A. Change the business rules so previously rejected inputs are accepted
- B. Improve the code's structure while retaining its existing behavior
- C. Replace the feature with a new workflow that returns different results
- D. Remove an existing validation requirement to simplify execution
Answer: B
Explanation: The module describes refactoring assistance as "Handles sophisticated code transformations while preserving functionality". Changing requirements or accepted results is a functional change, rather than the stated refactoring goal.
Reference: Boost developer productivity with AI — Orchestrated AI workflows / Advanced reasoning capabilities / Complex refactoring assistance
6A repository collaborator has the Maintain role. What can they do with that repository's Copilot content exclusion settings?
- A. Edit repository exclusions but not view inherited ones
- B. Edit inherited organization exclusions for that repository
- C. View the settings but not edit them
- D. Edit exclusions after changing their local editor settings
7An AI-assisted development process must handle unexpected conditions without causing unintended harm. Which responsible AI principle most directly addresses this requirement?
- A. Reliability and safety
- B. Transparency
- C. Fairness
- D. Accountability
Answer: A
Explanation: Under reliability and safety, the module says, "These systems need to function as designed, respond safely to unexpected conditions, and resist harmful manipulation." The requirement concerns dependable and safe behavior.
Reference: Microsoft and GitHub's six principles of responsible AI — Reliability and safety: AI systems should perform reliably and safely
8With the default VS Code keybinding, how do you accept a displayed Copilot ghost text suggestion?
- A. Press Escape
- B. Press Tab
- C. Press Ctrl+F
- D. Press Shift+Tab
9When enabled Copilot Chat web search is used, what information flow does GitHub describe?
- A. The browser sends only its locale, without prompt-derived content
- B. The search engine receives only the finished answer after generation
- C. The prompt and context generate a query sent to Bing
- D. The model searches solely within its training weights offline
Answer: C
Explanation: The card says, "the content of your prompt, along with additional context, is used to generate a Bing search query on your behalf." Search therefore involves prompt-derived information leaving the conversation for the search service.
Reference: Application card: GitHub Copilot Chat — 7. Limitations / Leveraging web search
10You give Copilot several input-output examples before requesting a new result. Which prompting approach are you using?
- A. Zero-shot prompting, because examples replace instructions
- B. Model fine-tuning, because examples permanently update weights
- C. Few-shot prompting, because examples demonstrate the desired behavior
- D. Output validation, because examples prove the generated result is correct
Answer: C
Explanation: Microsoft explains that few-shot learning involves "including one or more examples of the desired behavior of the model, typically by including input and output pairs." These examples condition the current inference; prompts without examples are zero-shot.
Reference: Prompt engineering techniques — Basics / Examples
Topics in this practice bank
These topics describe the available practice for Exam GH-300: GitHub Copilot. Review the examination outline and its sources for scope and allocation details.
Use GitHub Copilot responsibly
- Understand responsible AI principles
- Validate and operate AI tools
Use GitHub Copilot features
- Use GitHub Copilot in the IDE
- Use GitHub Copilot CLI
- Use GitHub Copilot features and capabilities
- Manage organization-wide settings and policies
Understand GitHub Copilot data and architecture
- Describe data handling and flow
- Understand lifecycle and limitations
Apply prompt engineering and context crafting
- Craft effective prompts
- Engineer prompts for performance
Improve developer productivity with GitHub Copilot
- Enhance productivity and code quality
- Support testing and security
Configure privacy, content exclusions, and safeguards
- Manage privacy settings and exclusions
- Apply safeguards and troubleshoot
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These are independent study questions, not actual examination items. For examination requirements and official information, view Exam GH-300: GitHub Copilot details.