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2026 Excellent GH-300–100% Free New Exam Prep | Exam GitHub Copilot Registration

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Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
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	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 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	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.

 

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Microsoft GitHub Copilot Sample Questions (Q95-Q100):

NEW QUESTION # 95
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.)

• A. Code that contains logical errors or produces unexpected results
• B. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)
• C. Sexually suggestive or explicit content
• D. Code comments containing strong opinions or criticisms

Answer: B,C

Explanation:
GitHub Copilot includes a toxicity filter to prevent the generation of harmful or inappropriate content. This filter flags prompts or code snippets that contain hate speech, discriminatory language, or sexually suggestive or explicit content. This ensures a safe and respectful coding environment.

 

NEW QUESTION # 96
When using GitHub Copilot to identify missing tests in your codebase, which of the following is the most important factor to consider?

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

Answer: D

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 # 97
Which Microsoft ethical AI principle is aimed at ensuring AI systems treat all people equally?

• A. Inclusiveness
• B. Reliability and Safety
• C. Fairness
• D. Privacy and Security

Answer: C

Explanation:
"Fairness. AI systems should treat all people fairly." This principle directly defines fairness as the standard for ensuring equality across all individuals.
References: Microsoft Responsible AI principles.

 

NEW QUESTION # 98
What GitHub Copilot feature can be configured at the organization level to prevent GitHub Copilot suggesting publicly available code snippets?

• A. GitHub Copilot duplication detection filter
• B. GitHub Copilot Chat in the IDE
• C. GitHub Copilot Chat in GitHub Mobile
• D. GitHub Copilot access to Bing

Answer: A

Explanation:
The duplication detection filter can be configured at the organization level to prevent GitHub Copilot from suggesting publicly available code snippets.

 

NEW QUESTION # 99
How does GitHub Copilot utilize chat history to enhance its code completion capabilities?

• A. By analyzing past chat interactions to identify common programming patterns and errors.
• B. By sharing chat history with third-party services to improve integration and functionality.
• C. By using chat history to offer personalized code snippets based on previous prompts.
• D. By logging chat history to monitor user activity and ensure compliance with coding standards.

Answer: A

Explanation:
"GitHub Copilot Chat can reference the ongoing conversation history to analyze patterns, common coding styles, and errors, providing more accurate and contextual suggestions." This demonstrates that chat history is used to identify patterns and enhance contextual accuracy, making option C correct.
References: GitHub Copilot Chat documentation.

 

NEW QUESTION # 100
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