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GitHub-Copilot High Quality | GitHub-Copilot Free Sample Questions

Hundreds of candidates want to get the GitHub CopilotCertification Exam (GitHub-Copilot) certification exam because it helps them in accelerating their GitHub careers. Cracking the GitHub-Copilot exam of this credential is vital when it comes to the up gradation of their resume. The GitHub-Copilot Certification Exam helps students earn from online work and it also benefits them in order to get a job in any good tech company.

GitHub GitHub-Copilot Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

Developer Use Cases for AI: This section of the exam measures skills of Full-Stack Developers and Cloud Engineers and covers how AI enhances developer productivity across various tasks such as learning new programming languages, debugging, writing documentation, and refactoring code. It discusses how GitHub Copilot integrates with the Software Development Lifecycle (SDLC) and its role in modernizing legacy applications. It also highlights the use of AI for personalized responses, sample data generation, and improving overall efficiency in software development.

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.

Topic 4

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.

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GitHub CopilotCertification Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)

A. Provide specific success criteria
B. Provide insight on where to get the content from to get a response
C. Provide all information about the utilized files
D. Provide links to supporting documentation

Answer: A,D

Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.

NEW QUESTION # 21
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)

A. By adding comments to your code and triggering a suggestion.
B. By highlighting the code you want to fix, right-clicking, and selecting "Fix using GitHub Copilot."
C. By using the "/fix" command in GitHub Copilot in-line chat.
D. By running the gh copilot fix command.
E. By highlighting the code you want to fix, right-clicking, and selecting "Refactor using GitHub Copilot."

Answer: A,E

Explanation:
You can use GitHub Copilot for inline refactoring suggestions by adding comments to your code to trigger suggestions and by highlighting the code and selecting "Refactor using GitHub Copilot" from the context menu.

NEW QUESTION # 22
Which REST API endpoint is used to modify details about a GitHub Copilot Business subscription? (Each correct answer presents part of the solution. Choose two.)

A. Add teams to the Copilot subscription for an organization
B. Remove teams from the Copilot subscription for an organization
C. Reassign Copilot seats based on GitHub repository size
D. Upgrade or downgrade the subscription tier
E. Migrate Copilot seat assignments between GitHub organizations

Answer: A,B

Explanation:
The REST API endpoints are used to add and remove teams from the Copilot Business subscription within an organization.

NEW QUESTION # 23
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 refactor applications to align with upcoming standards.
C. GitHub Copilot can directly convert legacy applications into cloud-native architectures.
D. GitHub Copilot can create and deploy full-stack applications based on a single query.

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,Bis 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 # 24
Which of the following is a risk associated with using AI?

A. AI replaces the need for developer opportunities in most fields.
B. AI eliminates the need for data privacy regulations.
C. AI algorithms are incapable of perpetuating existing biases.
D. AI systems can sometimes make decisions that are difficult to interpret.

Answer: D

Explanation:
A risk associated with AI is that its decisions can be difficult to interpret, leading to a lack of transparency and potential misunderstandings.

NEW QUESTION # 25
......

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