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Valid GH-300 Test Topics | New Guide GH-300 Files

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Microsoft GH-300 Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

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 4

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.

Topic 5

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 6

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.

>> Valid GH-300 Test Topics <<

Valid Microsoft GH-300 Questions - Prepare Effectively For Exam

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Microsoft GitHub Copilot Sample Questions (Q80-Q85):

NEW QUESTION # 80
How does GitHub Copilot assist developers in minimizing context switching?

A. GitHub Copilot allows developers to stay in their IDE.
B. GitHub Copilot can predict and prevent bugs before they occur.
C. GitHub Copilot can completely replace the need for human collaboration.
D. GitHub Copilot can automatically handle project management tasks.

Answer: A

Explanation:
"Copilot reduces the need to switch between documentation, browsers, and editors by bringing suggestions and explanations directly into the IDE." This demonstrates that minimizing context switching comes from enabling developers to stay within their IDE.
References: GitHub Copilot productivity documentation.

NEW QUESTION # 81
How does GitHub Copilot Chat ensure that a function works correctly?

A. By writing the implementation code for the function.
B. By automatically writing all the tests for the function.
C. By executing the test cases to validate the correctness of the code.
D. By suggesting assertions based on the code's context and semantics.

Answer: D

Explanation:
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.
Reference: GitHub Copilot documentation on testing and code verification.

NEW QUESTION # 82
What kind of insights can the GitHub Copilot usage metrics API provide to help evaluate the effectiveness of GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

A. The API can refactor your code to improve productivity.
B. The API can track the number of code suggestions accepted and used in the organization.
C. The API can generate detailed reports on code quality improvements made by GitHub Copilot.
D. The API can provide Copilot Chat specific suggestions acceptance metrics.
E. The API can provide feedback on coding style and standards compliance.

Answer: B,D

Explanation:
Exact extracts:
* "The Copilot usage metrics API allows organizations to track the number of suggestions shown and accepted by members." References: GitHub Copilot metrics API documentation.

NEW QUESTION # 83
How does GitHub Copilot Chat ensure that a function works correctly?

A. By writing the implementation code for the function.
B. By automatically writing all the tests for the function.
C. By executing the test cases to validate the correctness of the code.
D. By suggesting assertions based on the code's context and semantics.

Answer: D

NEW QUESTION # 84
How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?

A. It primarily uses search results from Bing to generate responses.
B. It uses user-provided documentation exclusively to generate responses.
C. It combines its training data set, code in user repositories, and external sources like Bing to generate responses.
D. It primarily relies on the model's training data to generate responses.

Answer: C

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.

NEW QUESTION # 85
......

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