2026 New GH-300 Dumps - Real Microsoft Exam Questions [Q56-Q73]

2026 New GH-300 Dumps - Real Microsoft Exam Questions

Dependable GH-300 Exam Dumps to Become Microsoft Certified

Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
Topic 1	Domain 4: Prompt Crafting and Prompt Engineering This section measures skills of Software Developers and AI Interaction Designers in effectively crafting prompts to optimize Copilot’s output. It reviews foundational concepts such as prompt components, the role of language in prompting, zero-shot vs. few-shot prompting, and how chat history influences responses. Best practices and engineering principles for prompt design and training methods are also covered.
Topic 2	GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
Topic 3	Responsible :This section of the exam measures skills of AI Ethics Officers and Risk Managers and covers the responsible and ethical usage of AI technologies. It explains the risks and limitations associated with generative AI tools, including biases in training data and the need to validate AI outputs. Candidates learn how to operate AI responsibly by identifying potential harms such as bias, fairness, privacy concerns, and mitigating these harms by applying ethical AI principles.
Topic 4	Privacy Fundamentals and Context Exclusions: This domain focuses on Security Engineers and Compliance Officers and addresses improving code quality with Copilot’s test suggestions and security optimizations. It covers identification of security vulnerabilities, performance enhancements, and privacy features like content exclusions at repository and organization levels with explanation of their limitations. Candidates learn about safeguarding mechanisms such as duplication detection, contractual protections, security checks, and troubleshooting guide for common Copilot issues including context exclusions and suggestion gaps.
Topic 5	How GitHub Copilot Works and Handles Data: Designed for Machine Learning Engineers and Data Privacy Specialists, this section covers the data lifecycle and processing behind Copilot’s code suggestions. It explains how context is gathered, prompts constructed, responses generated, and post-processed through proxy services. Candidates understand Copilot’s data policies, handling of inputs, and limitations such as context window size and data age influencing suggestion relevance.

 

NEW QUESTION # 56
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

• A. Creation of end-to-end performance testing scenarios for a web application
• B. Create a technical requirement specification from the business requirement documentation
• C. Explain a legacy COBOL code and translate the code to another language like Python.
• D. Creation of a unit test scenario for newly developed Python code

Answer: C,D

Explanation:
GitHub Copilot Chat is effective for explaining and translating legacy code and generating unit test scenarios for new code.
Reference: GitHub Copilot Chat use cases.

NEW QUESTION # 57
Why is it important to ensure the security of the code used in Generative AI (Gen AI) tools?

• A. Ensuring code security maintains the integrity of the AI system.
• B. Ensuring code security prevents unauthorized access and potential data breaches.
• C. Ensuring code security supports the development of more advanced AI features.
• D. Ensuring code security enables the AI system to handle larger datasets effectively.

Answer: B

Explanation:
"Securing the code used with generative AI prevents unauthorized access, helps safeguard sensitive data, and protects against potential breaches." This confirms option A is correct because the primary importance lies in avoiding unauthorized access and breaches.
References: GitHub Copilot responsible use and AI security documentation.

NEW QUESTION # 58
A company is currently storing code in Bitbucket and would like to use GitHub Copilot. Which GitHub Copilot plan will be most cost effective to allow them to manage users with their Identity Provider (e.g. Okta)?

• A. GitHub Copilot Enterprise
• B. GitHub Copilot Teams
• C. GitHub Copilot Business for non-GHE customers
• D. GitHub Copilot Individual

Answer: A

Explanation:
GitHub Copilot Enterprise is the most cost-effective plan for managing users with an Identity Provider like Okta, as it provides enterprise-level features and integration.
Reference: GitHub Copilot pricing and features.

NEW QUESTION # 59
In what ways can GitHub Copilot support a developer during the code refactoring process? (Each correct answer presents part of the solution. Choose two.)

• A. By autonomously refactoring entire codebases to the latest programming language.
• B. By independently ensuring compliance with regulatory standards across industries.
• C. By offering code transformation examples that enhance performance and reduce complexity.
• D. By providing suggestions for improving code readability and maintainability based on best practices.

Answer: C,D

Explanation:
Exact extracts:
* "Copilot can propose code transformations that improve performance and reduce complexity." References: GitHub Copilot code refactoring documentation.

NEW QUESTION # 60
What GitHub Copilot pricing plan gives you access to your company's knowledge bases?

• A. GitHub Copilot Enterprise
• B. GitHub Copilot Business
• C. GitHub Copilot Professional
• D. GitHub Copilot Individual

Answer: A

Explanation:
GitHub Copilot Enterprise provides access to your company's knowledge bases, enabling the tool to provide contextually relevant suggestions based on your organization's specific documentation and code.

NEW QUESTION # 61
What is few-shot prompting?

• A. Telling GitHub Copilot about the mechanism you want it to use and how to incorporate that into the response
• B. Telling GitHub Copilot to try multiple times to answer the prompt
• C. Telling GitHub Copilot from which sources it should base the response on
• D. Telling GitHub Copilot to iterate several times on the answer before returning it to you

Answer: A

Explanation:
"Few-shot prompting is a technique where you provide examples of the mechanism or output you want the model to follow. These examples guide the AI's responses." This proves that option A is correct.
References: GitHub Copilot prompt engineering documentation.

NEW QUESTION # 62
When can GitHub Copilot still use content that was excluded using content exclusion?

• A. When the user prompts with @workspace.
• B. When the repository-level settings allow overrides by the user.
• C. If the contents of an excluded file are referenced in code that is not excluded, for example function calls.
• D. If the content exclusion was configured at the enterprise level, and is overwritten at the organization level.

Answer: C

Explanation:
"If excluded content is referenced by non-excluded code, such as through function calls, Copilot may still use that reference context." This confirms that excluded content can indirectly appear if referenced elsewhere.
References: GitHub Copilot content exclusions limitations documentation.

NEW QUESTION # 63
How can GitHub Copilot assist with code refactoring tasks?

• A. GitHub Copilot can remove unnecessary files from the project directory.
• B. GitHub Copilot can fix syntax errors without user input.
• C. GitHub Copilot can suggest refactoring improvements for better code quality.
• D. GitHub Copilot can automatically rewrite code to follow best practices.

Answer: C

Explanation:
GitHub Copilot can analyze existing code and suggest refactoring improvements to enhance code quality, readability, and maintainability. It can propose changes to improve code structure, reduce complexity, and follow best practices.

NEW QUESTION # 64
How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

• A. It can validate the accuracy of the changes in the pull request.
• B. It automatically merges pull requests after an automated review.
• C. It can answer questions about the changeset of the pull request.
• D. It generates a prose summary and a bulleted list of key changes for pull requests.

Answer: C,D

Explanation:
GitHub Copilot Enterprise assists in code reviews by generating summaries of pull requests and answering questions about the changes made.

NEW QUESTION # 65
How do you generate code suggestions with GitHub Copilot in the CLI?

• A. Describe the project's architecture -> Use the copilot generate command -> Accept the generated suggestion.
• B. Write code comments -> Press the suggestion shortcut -> Select the best suggestion from the list.
• C. Use copilot suggest -> Write the command you want -> Select the best suggestion from the list.
• D. Type out the code snippet -> Use the copilot refine command to enhance it -> Review the suggested command.

Answer: B

Explanation:
In the CLI, GitHub Copilot generates code suggestions by analyzing code comments. You write comments describing what you want, and Copilot provides relevant code suggestions. You then select the best suggestion from the list.
Reference: GitHub Copilot CLI documentation.

NEW QUESTION # 66
How does GitHub Copilot suggest code optimizations for improved performance?

• A. By analyzing the codebase and suggesting more efficient algorithms or data structures.
• B. By providing detailed reports on the performance of the codebase.
• C. By automatically rewriting the codebase to use more efficient code.
• D. By enforcing strict coding standards that ensure optimal performance.

Answer: A

Explanation:
GitHub Copilot suggests code optimizations by analyzing the codebase and recommending more efficient algorithms or data structures.
Reference: GitHub Copilot code optimization documentation.

NEW QUESTION # 67
What can be done during AI development to minimize bias?

• A. Use diverse data, fairness metrics, and human oversight.
• B. Improve on the computational efficiency and speed.
• C. Collect massive amounts of data for training.
• D. Focus on accuracy of the data.

Answer: A

Explanation:
"Minimizing bias requires diverse datasets, use of fairness metrics, and human oversight throughout development and deployment." This clearly confirms that the proper approach is a combination of diverse data, fairness metrics, and oversight.
References: Microsoft Responsible AI and GitHub Copilot fairness guidelines.

NEW QUESTION # 68
Where is the proxy service hosted?

• A. Amazon Web Service
• B. Microsoft Azure
• C. Self hosted
• D. Google Cloud Platform

Answer: B

Explanation:
The proxy service for GitHub Copilot is hosted on Microsoft Azure.

NEW QUESTION # 69
Which of the following is a risk associated with using AI?

• A. AI replaces the need for developer opportunities in most fields.
• B. AI systems can sometimes make decisions that are difficult to interpret.
• C. AI eliminates the need for data privacy regulations.
• D. AI algorithms are incapable of perpetuating existing biases.

Answer: B

Explanation:
A risk associated with AI is that its decisions can be difficult to interpret, leading to a lack of transparency and potential misunderstandings.
Reference: AI risk management documentation.

NEW QUESTION # 70
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

• A. Use the emojis in the Copilot Chat interface.
• B. The Settings menu in the GitHub Mobile app.
• C. By tweeting at GitHub's official X (previously known as Twitter) account.
• D. The feedback section on the GitHub website.

Answer: A

Explanation:
The best way to share feedback on GitHub Mobile is using the emojis in the Copilot Chat interface, which allows for direct and immediate feedback.
Reference: GitHub Copilot Mobile documentation.

NEW QUESTION # 71
When using GitHub Copilot to identify missing tests in your codebase, which of the following is the most important factor to consider?

• A. Ensuring that the correct context is available to GitHub Copilot.
• B. Close all the tabs in your IDE that do not have tests in them.
• C. Having a high test coverage percentage in the codebase.
• D. Using well-known coding practices in your repository.

Answer: A

Explanation:
"The accuracy of Copilot's test generation depends heavily on the available context, including existing code, file structure, and open selections." This confirms that providing the correct context is the most important factor.
References: GitHub Copilot testing documentation.

NEW QUESTION # 72
What specific function does the /fix slash command perform?

• A. Proposes changes for detected issues, suggesting corrections for syntax errors and programming mistakes.
• B. Initiates a code review with static analysis tools for security and logic errors.
• C. Converts pseudocode into executable code, optimizing for readability and maintainability.
• D. Generates new code snippets based on language syntax and best practices.

Answer: A

Explanation:
"/fix: Propose changes to resolve detected issues, such as syntax errors or common programming mistakes, in the selected code." This confirms that the /fix command is used to suggest corrections for identified problems.
References: GitHub Copilot Chat command reference.

NEW QUESTION # 73
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