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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
  • 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
  • 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
  • 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
  • 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 (Q32-Q37):

NEW QUESTION # 32
How can GitHub Copilot assist with code refactoring tasks?

Answer: A

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 # 33
Which GitHub Copilot pricing plans include features that exclude your GitHub Copilot data like usage, prompts, and suggestions from default training GitHub Copilot? (Choose two correct answers.)

Answer: C,D

Explanation:
"For Copilot Business and Copilot Enterprise, user data such as code suggestions, prompts, and completions are excluded from training GitHub Copilot's models." This confirms that only Business and Enterprise plans provide this exclusion feature.
References: GitHub Copilot data usage and privacy documentation.


NEW QUESTION # 34
When using GitHub Copilot Chat to generate unit tests, which slash command would you use?

Answer: B

Explanation:
"/tests: Generate unit tests for the selected code or function."
This is the official description of the /tests slash command, confirming it is the command used to create unit tests.
References: GitHub Copilot Chat slash command reference.


NEW QUESTION # 35
When crafting prompts for GitHub Copilot, what is a recommended strategy to enhance the relevance of the generated code?

Answer: B

Explanation:
"To get the best results from GitHub Copilot, provide clear prompts and, when possible, include examples of expected input and output." This establishes that including examples is a recommended prompt engineering strategy.
References: GitHub Copilot prompt engineering documentation.


NEW QUESTION # 36
Where is the proxy service hosted?

Answer: A

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


NEW QUESTION # 37
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