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Guide for GH-300: Microsoft GitHub Foundations

Quiz GH-300: Microsoft GitHub Foundations

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Quiz

1/10
Your development team is using GitHub Copilot to generate code for a financial services application. A
developer notices that Copilot occasionally suggests code patterns that match publicly available financial
processing libraries almost verbatim. Your team wants to ensure they are using Copilot responsibly and
meeting both ethical and legal requirements. Which of the following actions should you take to mitigate this
risk? (Select all that apply)
Select the answer
3 correct answers
A.
Enable the 'Suggestions matching public code' filter to reduce suggestions that closely match public repositories
B.
Review and validate all generated code to ensure it is appropriate for your use case and does not introduce unintended dependencies
C.
Disable GitHub Copilot entirely, since any AI-generated code inherently poses legal and ethical risks
D.
Require developers to manually cross-reference every Copilot suggestion against public code repositories before using it
E.
Document your use of Copilot and the validation process in your development workflow to ensure accountability

Quiz

2/10
Your development team uses GitHub Copilot for code generation and has noticed that some suggestions
match code from popular open-source projects that use permissive licenses. A team member expresses
concern about potential license compliance issues. Which combination of actions should your team take to
operate GitHub Copilot responsibly in this scenario?
Select the answer
1 correct answer
A.
Enable public code filtering in GitHub Copilot settings to reduce suggestions matching public repositories, and establish a review process to evaluate Copilot suggestions for license compatibility before merging
B.
Disable GitHub Copilot entirely to eliminate all risk of license compliance issues, and only write code manually from scratch
C.
Accept all Copilot suggestions without review since the tool is trained on licensed data and Microsoft assumes all legal responsibility
D.
Configure content exclusions to block all open-source files, then use Copilot only for proprietary code generation

Quiz

3/10
A software architect is setting up GitHub Copilot for a new team and needs to ensure that certain proprietary
files containing trade secrets are never used as context for code suggestions. The architect also wants to
enable Copilot Chat and inline suggestions in the IDE. Which configuration approach should the architect
implement?
Select the answer
1 correct answer
A.
Configure content exclusions at the repository level to exclude files containing trade secrets from Copilot context, then enable Copilot Chat and inline suggestions in IDE settings
B.
Disable GitHub Copilot Chat entirely and only use inline suggestions, which are not affected by proprietary code
C.
Store all trade secrets in a separate repository and rely solely on code review to prevent Copilot from using proprietary context
D.
Configure proxy filtering to block all file types, then manually select which suggestions to accept

Quiz

4/10
A developer is using GitHub Copilot CLI to generate deployment scripts for a cloud infrastructure project. The
developer wants to review the generated script, test it in a staging environment, and understand the
reasoning behind Copilot's suggestions before applying it to production. What is the most responsible
approach to validate and operate the tool in this scenario?
Select the answer
1 correct answer
A.
Use GitHub Copilot CLI to generate the script, manually review the output for correctness and security issues, test it in staging with proper error handling, and validate that it meets project requirements before production deployment
B.
Accept the GitHub Copilot CLI output and deploy it directly to production since the tool is generated by Microsoft's AI model
C.
Use GitHub Copilot CLI only to generate documentation comments, not executable code, to avoid operational risks
D.
Run the script in production with monitoring enabled to catch errors in real time rather than testing in staging first

Quiz

5/10
Your organization is using GitHub Copilot to assist developers across multiple teams. A junior developer
generates unit tests with Copilot's help, but some test cases do not cover edge cases or negative scenarios.
When you review the tests before they are merged, you notice that Copilot's suggestions have limitations in
understanding complex business logic edge cases. What does this scenario best illustrate about generative
AI and how should you respond?
Select the answer
1 correct answer
A.
It illustrates a limitation of LLMs that they may generate syntactically correct but semantically incomplete test coverage. The team should augment Copilot suggestions with manual review to identify and add missing edge cases and assertions
B.
It shows that GitHub Copilot should never be used for test generation, and tests must always be written entirely by hand
C.
It demonstrates that LLMs are fully capable of understanding business logic, and the developer should have provided more context in the prompt
D.
It indicates that Copilot outputs should be deployed without review as long as they pass automated testing

Quiz

6/10
You are preparing to deploy GitHub Copilot across your organization and need to configure organization-wide
settings to control which features are available to developers. You want to enable GitHub Copilot Code
Review as a policy across all teams, manage IDE availability (VS Code, JetBrains, etc.), and track feature
usage through audit logs. Which of the following capabilities should you use to achieve these goals?
Select the answer
1 correct answer
A.
Use GitHub organization settings to configure Copilot policies, enable Code Review policies specifically, set IDE feature availability, and review audit log events to track organization-wide Copilot usage
B.
Manually configure GitHub Copilot on each developer's machine using local IDE settings, then ask developers to self-report their usage
C.
Deploy a custom proxy server to intercept all Copilot requests and manually approve each suggestion before it reaches developers
D.
Rely on individual team leads to manage Copilot settings within their teams without organization-wide policy enforcement

Quiz

7/10
Which of the following describes role prompting?
Select the answer
1 correct answer
A.
Describing in your prompt what your role is to get a better suggestion
B.
Tell GitHub Copilot in what tone of voice it should respond
C.
Prompt GitHub Copilot to explain what was the role of a suggestion
D.
Giving GitHub Copilot multiple examples of the form of the data you want to use

Quiz

8/10
Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?
Select the answer
1 correct answer
A.
A complete replacement for developers generating code.
B.
A productivity tool that provides suggestions, but relying on human judgment.
C.
A solution for software development, requiring no additional input or oversight.
D.
A tool solely designed for debugging and error correction.

Quiz

9/10
How long does GitHub retain Copilot data for Business and Enterprise? (Each correct answer presents
part of the solution. Choose two.)
Select the answer
2 correct answers
A.
Prompts and Suggestions: Not retained
B.
Prompts and Suggestions: Retained for 28 days
C.
User Engagement Data: Kept for Two Years
D.
User Engagement Data: Kept for One Year

Quiz

10/10
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.)
Select the answer
2 correct answers
A.
Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)
B.
Sexually suggestive or explicit content
C.
Code that contains logical errors or produces unexpected results
D.
Code comments containing strong opinions or criticisms
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  • Quiz name:GH-300: Microsoft GitHub Foundations
  • Total number of questions:120
  • Number of questions for the test:50
  • Pass score:80%

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