Exam GitHub-Copilot Quick Prep - Latest GitHub-Copilot Test Dumps

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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
Topic 1	Responsible AI: This section of the exam measures the skills of AI Ethics Analysts and AI Developers and covers the principles of responsible AI usage, the risks associated with AI, and the limitations of generative AI tools. It includes the importance of validating AI-generated outputs and operating AI systems responsibly. It also explores potential harms such as bias, privacy concerns, and fairness issues, along with methods to mitigate these risks. The ethical considerations of AI development and deployment are also discussed.
Topic 2	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 3	How GitHub Copilot Works and Handles DataThis section of the exam measures the skills of Data Security Specialists and DevOps Engineers and covers how GitHub Copilot processes data, handles code suggestions and manages privacy concerns. It explains the data pipeline for Copilot’s suggestions, how it gathers context, and how prompts are processed through its AI model. The section also discusses the limitations of AI-generated code, the effects of historical data on suggestions, and the role of prompt crafting. Best practices for improving prompt effectiveness and optimizing AI-generated responses are included.
Topic 4	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.

GitHub CopilotCertification Exam Sample Questions (Q44-Q49):

NEW QUESTION # 44
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?

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

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 # 45
How can the concept of fairness be integrated into the process of operating an AI tool?

A. Regularly monitoring the AI tool's performance will ensure fairness in its outputs.
B. Focusing on accessibility will ensure fairness.
C. Focusing on collecting large datasets for training will ensure fairness.
D. Training AI data and algorithms to be free from biases will ensure fairness.

Answer: D

Explanation:
Fairness in AI tools is achieved by training the data and algorithms to be free from biases. This ensures that the tool treats all users equitably and avoids discriminatory outcomes.

NEW QUESTION # 46
Which Copilot Individual features are available when using a supported extension for Visual Studio, VS Code, or JetBrains IDEs? (Each correct answer presents part of the solution. Choose two.)

A. Knowledge Base
B. Pull Request Diff Analysis
C. Chat
D. Code suggestions

Answer: C,D

Explanation:
GitHub Copilot Individual provides code suggestions and chat features when used with supported IDE extensions like Visual Studio, VS Code, and JetBrains IDEs.

NEW QUESTION # 47
How long does GitHub retain Copilot data for Business and Enterprise? (Each correct answer presents part of the solution. Choose two.)

A. Prompts and Suggestions: Not retained
B. User Engagement Data: Kept for One Year
C. Prompts and Suggestions: Retained for 28 days
D. User Engagement Data: Kept for Two Years

Answer: C,D

Explanation:
For GitHub Copilot Business and Enterprise, prompts and suggestions are retained for 28 days to provide context and improve the service. User engagement data, which includes usage patterns and interactions, is kept for two years. This data retention policy is designed to balance service improvement with user privacy.

NEW QUESTION # 48
What is the process behind identifying public code matches when using a public code filter enabled in GitHub Copilot?

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

Answer: A

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 # 49
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Exam GitHub-Copilot Quick Prep - Latest GitHub-Copilot Test Dumps

Use Valid GitHub GitHub-Copilot Dumps PDF And Overcome Your Fear Of Taking Exam

GitHub GitHub-Copilot Exam Syllabus Topics:

GitHub CopilotCertification Exam Sample Questions (Q44-Q49):

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