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Microsoft GH-300 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | GitHub Copilot |
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| Exam Number: | GH-300 |
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| Certificate Validity Period: | 1 year |
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| Real Exam Qty: | 60–65 |
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| Available Languages: | Spanish, English, French, Korean, Chinese (Simplified), Japanese, Portuguese (Brazil), Arabic (Saudi Arabia), German |
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| Exam Duration: | 100 minutes |
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| Exam Price: | $99 USD |
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| Passing Score: | 700 / 1000 |
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| Exam Format: | Proctored, Scenario-based, Multiple-choice |
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| Recommended Training: | Microsoft Learn: GitHub Copilot Learning Path |
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| Exam Registration: | Microsoft Learn Exam Details Pearson VUE Registration |
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| Sample Questions: | Microsoft GH-300 Sample Questions |
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| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
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| Pre Condition: | Basic familiarity with GitHub, software development workflows, and at least one programming language; no formal prerequisites required |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300 |
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>> GH-300 Valid Braindumps Book <<
Free PDF Quiz 2026 Microsoft GH-300: High-quality GitHub Copilot Valid Braindumps Book
Microsoft GH-300 certification exams play a significant role to verify skills, experience, and knowledge in a specific technology. Enrollment in the GitHub Copilot GH-300 is open to everyone. Participants in the GitHub Copilot GH-300 come from all over the world and receive the credentials for the Microsoft GH-300. They can quickly advance their careers in the fiercely competitive market and benefit from certification after earning the GitHub Copilot GH-300 badge.
| Topic | Details |
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| Topic 1 | - 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.
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| Topic 2 | - 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.
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| Topic 3 | - 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.
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| Topic 4 | - 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.
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| Topic 5 | - 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.
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| Topic 6 | - 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 (Q76-Q81):
NEW QUESTION # 76
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?
- A. Suggest code snippets that reflect the most common practices in the training data.
- B. Suggest homogeneous solutions if provided a diverse data set.
- C. Suggest innovative coding solutions that are not yet popular.
- D. Suggest completely novel projects, while reducing time on a project.
Answer: A
Explanation:
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.
NEW QUESTION # 77
What configuration needs to be set to get help from Microsoft and GitHub protecting against IP infringement while using GitHub Copilot?
- A. Enable GitHub Copilot license checking
- B. Suggestions matching public code to 'blocked'
- C. Enforce blocking of MIT or GPL licensed code
- D. You need to check code suggestions yourself before accepting
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.
Reference: GitHub Copilot documentation on IP protection and code filtering.
NEW QUESTION # 78
What types of content can GitHub Copilot Knowledge Base answer questions about? (Each correct answer presents part of the solution. Choose three.)
- A. Documentation
- B. Compiled binaries
- C. Screenshots
- D. Code snippets
- E. Design patterns
Answer: A,D,E
Explanation:
"GitHub Copilot Knowledge Bases allow you to ask questions about your organization's documentation, design patterns, and code snippets." This proves that Copilot Knowledge Base can work with code snippets, documentation, and design patterns, but not binaries or screenshots.
References: GitHub Copilot Enterprise Knowledge Base documentation.
NEW QUESTION # 79
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. "Predict future coding trends and update my codebase accordingly."
- C. "Show me how to improve the readability of this function."
- D. "Suggest ways to enhance the maintainability of this code segment."
Answer: C,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 # 80
When using an IDE with a supported GitHub Copilot plug-in, which Chat features can be accessed from within the IDE? (Each correct answer presents part of the solution. Choose two.)
- A. Generate unit tests
- B. Plan coding tasks
- C. Explain code and suggest improvements
- D. Find out about releases and commits
Answer: A,C
Explanation:
Exact extracts:
* "In supported IDEs, you can ask Copilot Chat to explain code or suggest improvements." References: GitHub Copilot Chat IDE integration documentation.
NEW QUESTION # 81
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