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[General] Pass Guaranteed Quiz Microsoft - Professional GH-300 - GitHub Copilot Latest Lea

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【General】 Pass Guaranteed Quiz Microsoft - Professional GH-300 - GitHub Copilot Latest Lea

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Microsoft GH-300 Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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 3
  • How GitHub Copilot Works and Handles Data: Designed for Machine Learning Engineers and Data Privacy Specialists, this section covers the data lifecycle and processing behind Copilot’s code suggestions. It explains how context is gathered, prompts constructed, responses generated, and post-processed through proxy services. Candidates understand Copilot’s data policies, handling of inputs, and limitations such as context window size and data age influencing suggestion relevance.

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Microsoft GitHub Copilot Sample Questions (Q89-Q94):NEW QUESTION # 89
What method can a developer use to generate sample data with GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)
  • A. Utilize GitHub Copilot's capability to directly access and use databases to create sample data.
  • B. Leveraging GitHub Copilot's ability to independently initiate and manage data storage services.
  • C. Utilizing GitHub Copilot's ability to create fictitious information from patterns in training data.
  • D. Leveraging GitHub Copilot's suggestions to create data based on API documentation in the repository.
Answer: C,D
Explanation:
GitHub Copilot can generate sample data by creating fictitious information based on patterns in its training data and by using suggestions based on API documentation within the repository.

NEW QUESTION # 90
What GitHub Copilot configuration needs to be enabled to protect against IP infringements?
  • A. Allowing license check configuration
  • B. Blocking license check configuration
  • C. Allowing public code matches
  • D. Blocking public code matches
Answer: D
Explanation:
"By default, suggestions matching public code are allowed, but you can choose to block public code matches.
This setting can be enabled to reduce the risk of intellectual property infringement." This shows that enabling "Blocking public code matches" is the configuration required to protect against IP issues.
References: GitHub Copilot configuration settings documentation.

NEW QUESTION # 91
What is zero-shot prompting?
  • A. Giving GitHub Copilot examples of the algorithm and outcome you want to use
  • B. Giving GitHub Copilot examples of the problem you want to solve
  • C. Only giving GitHub Copilot a question as a prompt and no examples
  • D. Giving as little context to GitHub Copilot as possible
  • E. Telling GitHub Copilot it needs to show only the correct answer
Answer: C
Explanation:
"Zero-shot prompting means asking the model to perform a task without providing examples-only the question or task description is given." This confirms that the correct definition of zero-shot prompting is providing no examples, only a direct prompt.
References: GitHub Copilot and AI prompting documentation.

NEW QUESTION # 92
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?
  • A. GitHub Copilot can suggest modern programming patterns based on your code.
  • B. GitHub Copilot can directly convert legacy applications into cloud-native architectures.
  • C. GitHub Copilot can create and deploy full-stack applications based on a single query.
  • D. GitHub Copilot can refactor applications to align with upcoming standards.
Answer: A
Explanation:
GitHub Copilot and GitHub Copilot Chat are powerful AI-driven tools designed to assist developers by providing context-aware code suggestions and interactive support. Specifically, in the context of modernizing applications, GitHub Copilot excels at analyzing existing code and suggesting modern programming patterns, best practices, and syntax improvements that align with contemporary development standards. For example, it can recommend updates to outdated constructs, propose more efficient algorithms, or suggest frameworks and libraries that are widely used in modern application development.
Why not A? GitHub Copilot does not "directly convert" legacy applications into cloud-native architectures. It can assist by suggesting code changes or patterns that support such a transition, but it doesn't autonomously perform the full conversion process, which involves architectural decisions and deployment steps beyond its scope.
Why not C? While GitHub Copilot can generate code snippets and even larger portions of an application, it cannot create and deploy full-stack applications from a single query. It requires developer input, refinement, and integration to achieve a complete, deployable solution.
Why not D? GitHub Copilot can assist with refactoring by suggesting improvements to existing code, but it doesn't inherently "align with upcoming standards" in a predictive sense. Its suggestions are based on current best practices and the data it was trained on, not future standards that are yet to be defined.
Thus, B is the most accurate and realistic way GitHub Copilot aids developers in modernizing applications, leveraging its ability to provide relevant, context-based suggestions to update and improve codebases.

NEW QUESTION # 93
What is the primary role of the /optimize slash command in Visual Studio?
  • A. Automatically formats the code according to the selected style guide.
  • B. Translates code into a more performant language.
  • C. Enhances the performance of the selected code by analyzing its runtime complexity.
  • D. Summarizes your documentation into more maintainable and readable formats.
Answer: C
Explanation:
The /optimize slash command in Visual Studio enhances the performance of the selected code by analyzing its runtime complexity and suggesting improvements.

NEW QUESTION # 94
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