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Test GH-300 Guide Exam | Best Way to Pass Microsoft GH-300
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There are many users that are using GitHub Copilot (GH-300) exam questions and rated it as one of the best in the market. The customers are pleased with GitHub Copilot (GH-300) exam questions and all of them have passed the GitHub Copilot (GH-300) certification exam on the very first try.
Microsoft GH-300 Exam Syllabus Topics:| Topic | Details | | Topic 1 | - 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 2 | - 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 3 | - 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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Microsoft GitHub Copilot Sample Questions (Q48-Q53):NEW QUESTION # 48
What is a key consideration when relying on GitHub Copilot Chat's explanations of code functionality and proposed improvements?
- A. GitHub Copilot Chat uses a static database for generating explanations.
- B. The explanations are primarily derived from user-provided documentation.
- C. The explanations are dynamically updated based on user feedback.
- D. Reviewing and validating the generated output for accuracy and completeness.
Answer: D
Explanation:
While GitHub Copilot Chat can provide helpful explanations and suggestions, it's crucial to review and validate the generated output. Copilot's suggestions are based on its training data, and they may not always be perfectly accurate or complete. Human judgment is essential to ensure the quality and correctness of the code.
Reference: GitHub Copilot best practices and usage guidelines.
NEW QUESTION # 49
Select a strategy to increase the performance of GitHub Copilot Chat.
- A. Apply prompt engineering techniques to be more specific
- B. Optimize the usage of memory-intensive operations within generated code
- C. Limit the number of concurrent users accessing GitHub Copilot Chat
- D. Use a single GitHub Copilot Chat query to find resolutions for the collection of technical requirements
Answer: A
Explanation:
" erformance of Copilot Chat can be improved with prompt engineering. More specific prompts give more relevant and accurate answers." This confirms that applying prompt engineering techniques is the valid strategy.
References: GitHub Copilot Chat best practices documentation.
NEW QUESTION # 50
Which of the following statements correctly describes how GitHub Copilot Individual uses prompt data?
(Each correct answer presents part of the solution. Choose two.)
- A. Prompt data is used to train machine learning models for better code suggestions.
- B. Real-time user input helps generate context-aware code suggestions.
- C. Prompt data is stored unencrypted for faster processing.
- D. Prompt data is used internally by GitHub for improving the search engine.
Answer: A,B
Explanation:
Exact extracts:
* "For GitHub Copilot Individual, prompts and code completions may be retained and used to train machine learning models to improve Copilot." References: GitHub Copilot data usage and privacy documentation.
NEW QUESTION # 51
If you are working on open source projects, GitHub Copilot Individual can be paid:
- A. N/A - Copilot Individual is a free service for all open source projects
- B. Based on the payment method in your user profile
- C. Through an Azure Subscription
- D. Through an invoice or a credit card
Answer: B
Explanation:
"GitHub Copilot Individual subscriptions are billed using the payment method configured in your GitHub user profile." There is no free tier for open source projects, so option A is correct.
References: GitHub Copilot billing documentation.
NEW QUESTION # 52
What are the potential limitations of GitHub Copilot in maintaining existing codebases?
- A. GitHub Copilot might not fully understand the context and dependencies within a large codebase.
- B. GitHub Copilot's suggestions are always aware of the entire codebase.
- C. GitHub Copilot can independently manage and resolve all merge conflicts in version control.
- D. GitHub Copilot can refactor and optimize the entire codebase up to 10,000 lines of code.
Answer: A
Explanation:
"Copilot may not always understand the full context or complex dependencies in large codebases, and suggestions may require significant review." This proves that the main limitation is a lack of deep awareness of complex or large codebase contexts.
References: GitHub Copilot limitations documentation.
NEW QUESTION # 53
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