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[General] GH-300 Study Demo, Latest GH-300 Test Notes

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【General】 GH-300 Study Demo, Latest GH-300 Test Notes

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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
  • 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.
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.
Topic 4
  • 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 5
  • 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.
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 (Q14-Q19):NEW QUESTION # 14
What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?
  • A. GitHub Copilot can independently verify the statistical significance of results.
  • B. GitHub Copilot can design new statistical methods that have not been previously documented.
  • C. GitHub Copilot will automatically correct any statistical errors found in the user's initial code.
  • D. GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.
Answer: D
Explanation:
Developers should consider that GitHub Copilot's suggestions are based on statistical trends and may not always be accurate for specific datasets, requiring careful validation.
Reference: GitHub Copilot data analysis limitations.

NEW QUESTION # 15
What is the primary purpose of organization audit logs in GitHub Copilot Business?
  • A. To track the number of lines of code suggested by Copilot
  • B. To monitor administrator activities and actions within the organization
  • C. To monitor code conflicts across repositories
  • D. To assign software licenses within the organization
Answer: B
Explanation:
"Audit logs in Copilot Business allow enterprise and organization administrators to monitor administrator activities and configuration changes." This proves that their purpose is not line tracking or license assignment but monitoring admin activities.
References: GitHub Copilot Business administration documentation.

NEW QUESTION # 16
What method can be used to interact with GitHub Copilot?
  • A. By using chat capabilities in NeoVim
  • B. From a web browser at https://github.copilot.com
  • C. From a watch window in an IDE debug session
  • D. By using a properly configured GitHub CLI
Answer: A
Explanation:
GitHub Copilot is an AI-powered code completion tool that integrates directly into supported Integrated Development Environments (IDEs) and code editors, such as Visual Studio Code, JetBrains IDEs, NeoVim, and others. Developers interact with it through their coding environment, where it provides real-time code suggestions, autocompletions, and (in some cases) chat-like capabilities via extensions or plugins (e.g., GitHub Copilot Chat in supported editors).
Evaluation of Options:
* A. By using a properly configured GitHub CLIThe GitHub CLI (Command Line Interface) is a tool for interacting with GitHub repositories and workflows from the terminal, but it is not a method for interacting with GitHub Copilot. Copilot operates within code editors/IDEs, not through the CLI.
Incorrect.
* B. By using chat capabilities in NeoVimThis is partially correct. GitHub Copilot can be used in NeoVim with the appropriate plugin (e.g., the Copilot.vim plugin), and GitHub Copilot Chat-a feature that allows conversational interaction-may also be available depending on the setup and version.
However, "chat capabilities in NeoVim" alone is not the primary or standard way to describe Copilot interaction, as it's more about code suggestions than chat. This is the closest option but not perfectly precise.Partially correct.
* C. From a watch window in an IDE debug sessionThe "watch window" in an IDE is used during debugging to monitor variable values, not to interact with GitHub Copilot. Copilot provides suggestions while coding, not specifically in debug sessions or watch windows.Incorrect.
* D. From a web browser athttps://github.copilot.comThere is no such URL as "https://github.copilot.
com" dedicated to interacting with GitHub Copilot. Copilot is accessed via GitHub's authentication and integrated into editors/IDEs, not through a standalone web browser interface. Information about Copilot is available on GitHub's official site (e.g.,https://github.com/features/copilot), but interaction happens in the coding environment.Incorrect.
Reference: GitHub Copilot interaction documentation.

NEW QUESTION # 17
What content can be configured to be excluded with content exclusions? (Each correct answer presents part of the solution. Choose three.)
  • A. Gists
  • B. Files
  • C. Repositories
  • D. Lines in files
  • E. Folders
Answer: B,C,E
Explanation:
"Enterprise administrators can configure content exclusions to exclude entire repositories, folders, or specific files from being used by Copilot." This confirms that files, folders, and repositories can be excluded, but not individual lines or gists.
References: GitHub Copilot content exclusions documentation.

NEW QUESTION # 18
Why is it important to ensure the security of the code used in Generative AI (Gen AI) tools?
  • A. Ensuring code security prevents unauthorized access and potential data breaches.
  • B. Ensuring code security enables the AI system to handle larger datasets effectively.
  • C. Ensuring code security maintains the integrity of the AI system.
  • D. Ensuring code security supports the development of more advanced AI features.
Answer: A
Explanation:
"Securing the code used with generative AI prevents unauthorized access, helps safeguard sensitive data, and protects against potential breaches." This confirms option A is correct because the primary importance lies in avoiding unauthorized access and breaches.
References: GitHub Copilot responsible use and AI security documentation.

NEW QUESTION # 19
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