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Recommended GitHub-Copilot Exam Questions To Pass In First Try

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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic
Details

Topic 1

GitHub Copilot Plans and FeaturesThis section of the exam measures the skills of Software Engineers and IT Administrators and covers different GitHub Copilot plans, including Individual, Business, and Enterprise editions. It explains the integration of GitHub Copilot within IDEs and discusses key features such as inline chat, multiple suggestions, and exception handling. The section details the policies for managing GitHub Copilot within organizations, including auditing logs and API management. It also highlights advanced functionalities like knowledge bases for improved code quality and best practices for Copilot Chat usage.

Topic 2

Testing with GitHub Copilot: This section of the exam measures skills of QA Engineers and Test Automation Specialists and covers AI-assisted testing methodologies, including the generation of unit tests, integration tests, and edge case detection. It explains how GitHub Copilot improves test effectiveness by suggesting relevant assertions and boilerplate test cases. The section also discusses privacy considerations, organizational code suggestion settings, and best practices for configuring GitHub Copilot’s testing features.

Topic 3

Privacy Fundamentals and Context Exclusions: This section of the exam measures skills of Cybersecurity Specialists and Compliance Officers and covers privacy safeguards and content exclusion settings in GitHub Copilot. It explains how Copilot can identify security vulnerabilities, suggest optimizations, and enforce secure coding practices. It also includes details on content ownership, data filtering mechanisms, and exclusion configurations. The section concludes with troubleshooting guidelines for managing context exclusions and ensuring compliance with organizational security policies.

>> GitHub-Copilot Online Test <<

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GitHub CopilotCertification Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?

A. Suggest innovative coding solutions that are not yet popular.
B. Suggest code snippets that reflect the most common practices in the training data.
C. Suggest homogeneous solutions if provided a diverse data set.
D. Suggest completely novel projects, while reducing time on a project.

Answer: B

Explanation:
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.

NEW QUESTION # 25
How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

A. It automatically merges pull requests after an automated review.
B. It can validate the accuracy of the changes in the pull request.
C. It can answer questions about the changeset of the pull request.
D. It generates a prose summary and a bulleted list of key changes for pull requests.

Answer: C,D

Explanation:
GitHub Copilot Enterprise assists in code reviews by generating summaries of pull requests and answering questions about the changes made.

NEW QUESTION # 26
What GitHub Copilot pricing plan gives you access to your company's knowledge bases?

A. GitHub Copilot Enterprise
B. GitHub Copilot Professional
C. GitHub Copilot Business
D. GitHub Copilot Individual

Answer: A

Explanation:
GitHub Copilot Enterprise provides access to your company's knowledge bases, enabling the tool to provide contextually relevant suggestions based on your organization's specific documentation and code.

NEW QUESTION # 27
What is a key consideration when relying on GitHub Copilot Chat's explanations of code functionality and proposed improvements?

A. The explanations are primarily derived from user-provided documentation.
B. The explanations are dynamically updated based on user feedback.
C. Reviewing and validating the generated output for accuracy and completeness.
D. GitHub Copilot Chat uses a static database for generating explanations.

Answer: C

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.

NEW QUESTION # 28
What is the process behind identifying public code matches when using a public code filter enabled in GitHub Copilot?

A. Comparing suggestions against public code using machine learning.
B. Reviewing the user's browsing history to identify public repositories
C. Running code suggestions through filters designed to detect public code
D. Analyzing the context and structure of the code being written

Answer: C

Explanation:
When the public code filter is enabled, GitHub Copilot runs code suggestions through filters designed to detect matches with publicly available code. This helps prevent the generation of code that might infringe on copyright or licensing agreements.

NEW QUESTION # 29
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