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Microsoft GH-300 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GitHub Copilot
Exam Number:GH-300
Exam Price:$99 USD
Available Languages:Japanese, Korean, English, Portuguese (Brazil), Spanish
Certificate Validity Period:1 year (renewable)
Related Certifications:GitHub Actions
GitHub Foundations
Exam Format:Multiple-choice, Scenario-based
Passing Score:700 / 1000
Exam Duration:100 minutes
Real Exam Qty:65
Sample Questions:Microsoft GH-300 Sample Questions
Exam Way:Online proctored exam (Pearson VUE)
Pre Condition:No formal prerequisites. Microsoft recommends practical experience using GitHub Copilot in an IDE and a general understanding of software development principles.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-copilot

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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 4
  • 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.

Microsoft GitHub Copilot Sample Questions (Q125-Q130):

NEW QUESTION # 125
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?

Answer: A

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 # 126
What is the main purpose of the duplication detection filter in GitHub Copilot?

Answer: B


NEW QUESTION # 127
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)

Answer: A,D

Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.


NEW QUESTION # 128
How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?

Answer: B

Explanation:
GitHub Copilot Chat combines its training data, code from user repositories, and external sources like Bing to generate comprehensive and relevant responses to coding questions.
Reference: GitHub Copilot Chat documentation on data sources.


NEW QUESTION # 129
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

Answer: A,D

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


NEW QUESTION # 130
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