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Prepare for your exam certification with our GH-300 Certified Microsoft [Q33-Q50]

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Prepare for your exam certification with our GH-300 Certified Microsoft

Free Microsoft GH-300 Exam 2025 Practice Materials Collection


Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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 3
  • Domain 6: Testing with GitHub Copilot: This section measures abilities of QA Engineers and Test Automation Specialists to use Copilot for test generation, including unit and integration tests. It explains how Copilot can identify edge cases and assist in writing assertions. The domain also covers different Copilot subscription SKUs, privacy considerations, organizational code suggestion settings, and configuration files related to Copilot.
Topic 4
  • 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 5
  • Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilot’s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilot’s impact is also included.
Topic 6
  • 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.

 

NEW QUESTION # 33
Where is the proxy service hosted?

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

Answer: B

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


NEW QUESTION # 34
How do you generate code suggestions with GitHub Copilot in the CLI?

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

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.


NEW QUESTION # 35
What role does chat history play in GitHub Copilot's code suggestions?

  • A. Chat history is used to train the GitHub Copilot model in real-time.
  • B. Chat history is irrelevant to GitHub Copilot and does not affect its functionality.
  • C. Chat history is stored and shared with other users to enhance collaboration.
  • D. Chat history provides context to GitHub Copilot, improving the relevance and accuracy of its code suggestions.

Answer: D

Explanation:
Chat history provides valuable context to GitHub Copilot, helping it generate more relevant and accurate code suggestions based on previous interactions and conversations.


NEW QUESTION # 36
Which REST API endpoint is used to modify details about a GitHub Copilot Business subscription? (Each correct answer presents part of the solution. Choose two.)

  • A. Migrate Copilot seat assignments between GitHub organizations
  • B. Reassign Copilot seats based on GitHub repository size
  • C. Add teams to the Copilot subscription for an organization
  • D. Upgrade or downgrade the subscription tier
  • E. Remove teams from the Copilot subscription for an organization

Answer: C,E

Explanation:
The REST API endpoints are used to add and remove teams from the Copilot Business subscription within an organization.


NEW QUESTION # 37
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?

  • A. Inclusiveness
  • B. Fairness
  • C. Accountability
  • D. Transparency

Answer: D

Explanation:
The principle of transparency emphasizes that AI systems should be understandable and provide clear information about their operations. This ensures that users can understand how the AI arrives at its decisions and suggestions.


NEW QUESTION # 38
Which of the following prompts can be used to guide GitHub Copilot Chat in refactoring code for quality improvements? (Each correct answer presents part of the solution. Choose two.)

  • A. "Refactor my application to meet the latest coding standards."
  • B. "Suggest ways to enhance the maintainability of this code segment."
  • C. "Predict future coding trends and update my codebase accordingly."
  • D. "Show me how to improve the readability of this function."

Answer: B,D

Explanation:
Effective prompts for refactoring include requests that focus on specific quality improvements, such as readability and maintainability. These prompts guide GitHub Copilot to provide relevant and actionable suggestions.


NEW QUESTION # 39
How long does it take content exclusion to add or be updated?

  • A. 45 - 60 minutes
  • B. 60 - 90 minutes
  • C. 24 hours
  • D. Up to 30 minutes

Answer: D

Explanation:
Content exclusions typically take up to 30 minutes to be added or updated.


NEW QUESTION # 40
How does GitHub Copilot Chat ensure that a function works correctly?

  • A. By automatically writing all the tests for the function.
  • B. By executing the test cases to validate the correctness of the code.
  • C. By writing the implementation code for the function.
  • D. By suggesting assertions based on the code's context and semantics.

Answer: D

Explanation:
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.


NEW QUESTION # 41
What is the correct way to exclude specific files from being used by GitHub Copilot Business during code suggestions?

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

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 # 42
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?

  • A. GitHub Copilot can directly convert legacy applications into cloud-native architectures.
  • B. GitHub Copilot can create and deploy full-stack applications based on a single query.
  • C. GitHub Copilot can refactor applications to align with upcoming standards.
  • D. GitHub Copilot can suggest modern programming patterns based on your code.

Answer: D

Explanation:
GitHub Copilot and GitHub Copilot Chat are powerful AI-driven tools designed to assist developers by providing context-aware code suggestions and interactive support. Specifically, in the context of modernizing applications, GitHub Copilot excels at analyzing existing code and suggesting modern programming patterns, best practices, and syntax improvements that align with contemporary development standards. For example, it can recommend updates to outdated constructs, propose more efficient algorithms, or suggest frameworks and libraries that are widely used in modern application development.
Why not A? GitHub Copilot does not "directly convert" legacy applications into cloud-native architectures. It can assist by suggesting code changes or patterns that support such a transition, but it doesn't autonomously perform the full conversion process, which involves architectural decisions and deployment steps beyond its scope.
Why not C? While GitHub Copilot can generate code snippets and even larger portions of an application, it cannot create and deploy full-stack applications from a single query. It requires developer input, refinement, and integration to achieve a complete, deployable solution.
Why not D? GitHub Copilot can assist with refactoring by suggesting improvements to existing code, but it doesn't inherently "align with upcoming standards" in a predictive sense. Its suggestions are based on current best practices and the data it was trained on, not future standards that are yet to be defined.
Thus, B is the most accurate and realistic way GitHub Copilot aids developers in modernizing applications, leveraging its ability to provide relevant, context-based suggestions to update and improve codebases.


NEW QUESTION # 43
What is zero-shot prompting?

  • A. Giving as little context to GitHub Copilot as possible
  • B. Giving GitHub Copilot examples of the algorithm and outcome you want to use
  • C. Only giving GitHub Copilot a question as a prompt and no examples
  • D. Giving GitHub Copilot examples of the problem you want to solve
  • E. Telling GitHub Copilot it needs to show only the correct answer

Answer: C

Explanation:
Zero-shot prompting involves asking GitHub Copilot a question or giving a task without providing any examples. This relies on the model's pre-existing knowledge to generate a response.


NEW QUESTION # 44
What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?

  • A. GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.
  • B. GitHub Copilot will automatically correct any statistical errors found in the user's initial code.
  • C. GitHub Copilot can independently verify the statistical significance of results.
  • D. GitHub Copilot can design new statistical methods that have not been previously documented.

Answer: A

Explanation:
Developers should consider that GitHub Copilot's suggestions are based on statistical trends and may not always be accurate for specific datasets, requiring careful validation.


NEW QUESTION # 45
How long does GitHub retain Copilot data for Business and Enterprise? (Each correct answer presents part of the solution. Choose two.)

  • A. Prompts and Suggestions: Retained for 28 days
  • B. User Engagement Data: Kept for Two Years
  • C. Prompts and Suggestions: Not retained
  • D. User Engagement Data: Kept for One Year

Answer: A,B

Explanation:
For GitHub Copilot Business and Enterprise, prompts and suggestions are retained for 28 days to provide context and improve the service. User engagement data, which includes usage patterns and interactions, is kept for two years. This data retention policy is designed to balance service improvement with user privacy.


NEW QUESTION # 46
How does GitHub Copilot Chat help in understanding the existing codebase?

  • A. By automatically refactoring code to improve readability.
  • B. By providing visual diagrams of the code structure.
  • C. By running code linters and formatters.
  • D. By answering questions about the code and generating explanations.

Answer: D

Explanation:
GitHub Copilot Chat helps in understanding existing codebases by answering questions about the code and generating explanations. This allows developers to quickly grasp the functionality and structure of unfamiliar code.


NEW QUESTION # 47
What configuration needs to be set to get help from Microsoft and GitHub protecting against IP infringement while using GitHub Copilot?

  • A. You need to check code suggestions yourself before accepting
  • B. Suggestions matching public code to 'blocked'
  • C. Enable GitHub Copilot license checking
  • D. Enforce blocking of MIT or GPL licensed code

Answer: B

Explanation:
To help protect against IP infringement, you need to configure GitHub Copilot to block suggestions that match public code. This ensures that the generated code is not directly copied from publicly available sources.


NEW QUESTION # 48
Which GitHub Copilot plan allows for prompt and suggestion collection?

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

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 # 49
What is the primary role of the /optimize slash command in Visual Studio?

  • A. Summarizes your documentation into more maintainable and readable formats.
  • B. Translates code into a more performant language.
  • C. Enhances the performance of the selected code by analyzing its runtime complexity.
  • D. Automatically formats the code according to the selected style guide.

Answer: C

Explanation:
The /optimize slash command in Visual Studio enhances the performance of the selected code by analyzing its runtime complexity and suggesting improvements.


NEW QUESTION # 50
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