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GitHub CopilotCertification Exam Questions and Answers

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Questions # 1:

When can GitHub Copilot still use content that was excluded using content exclusion?

Options:

If the contents of an excluded file are referenced in code that is not excluded, for example function calls.

When the repository level settings allow overrides by the user.

If the content exclusion was configured at the enterprise level, and is overwritten at the organization level.

When the user prompts with @workspace.

Answer

Explanation

GitHub Copilot can still use excluded content if it is referenced in code that is not excluded, such as function calls.

[Reference: GitHub Copilot content exclusion documentation.]

Questions # 2:

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

Options:

Focusing on accessibility will ensure fairness.

Focusing on collecting large datasets for training will ensure fairness.

Regularly monitoring the AI tool's performance will ensure fairness in its outputs.

Training AI data and algorithms to be free from biases will ensure fairness.

Answer

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.

[Reference: Microsoft's AI principles and fairness guidelines.]

Questions # 3:

Which Microsoft ethical AI principle is aimed at ensuring AI systems treat all people equally?

Options:

Privacy and Security

Fairness

Reliability and Safety

Inclusiveness

Answer

Explanation

The principle of fairness ensures that AI systems treat all people equally and avoid discriminatory outcomes.

[Reference: Microsoft's AI principles and fairness guidelines.]

Questions # 4:

In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?

Options:

GitHub Copilot can directly convert legacy applications into cloud-native architectures.

GitHub Copilot can suggest modern programming patterns based on your code.

GitHub Copilot can create and deploy full-stack applications based on a single query.

GitHub Copilot can refactor applications to align with upcoming standards.

Answer

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.

[Reference: GitHub Copilot documentation on application modernization., ]

Questions # 5:

How long does it take content exclusion to add or be updated?

Options:

Up to 30 minutes

45 - 60 minutes

60 - 90 minutes

24 hours

Answer

Explanation

Content exclusions typically take up to 30 minutes to be added or updated.

[Reference: GitHub Copilot content exclusion documentation.]

Questions # 6:

Which GitHub Copilot plan allows for prompt and suggestion collection?

Options:

GitHub Copilot Individuals

GitHub Copilot Business

GitHub Copilot Enterprise

GitHub Copilot Codespace

Answer

Explanation

GitHub Copilot Enterprise allows for prompt and suggestion collection, enabling organizations to analyze and improve their usage of the tool.

[Reference: GitHub Copilot Enterprise data collection documentation.]

Questions # 7:

What is the correct way to access the audit log events for GitHub Copilot Business?

Options:

Navigate to the Security tab in the organization's GitHub settings

Navigate to the Insights tab in the repository settings

Use the Audit log section in the organization's GitHub settings

Use the Code tab in the GitHub repository

Answer

Explanation

Audit log events for GitHub Copilot Business can be accessed through the Audit log section within the organization's GitHub settings. This log provides a record of activities related to Copilot usage and configuration.

[Reference: GitHub Copilot Business documentation on audit logs.]

Questions # 8:

What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?

Options:

GitHub Copilot can independently verify the statistical significance of results.

GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.

GitHub Copilot will automatically correct any statistical errors found in the user's initial code.

GitHub Copilot can design new statistical methods that have not been previously documented.

Answer

Explanation

Developers should consider that GitHub Copilot's suggestions are based on statistical trends and may not always be accurate for specific datasets, requiring careful validation.

[Reference: GitHub Copilot data analysis limitations.]

Questions # 9:

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

Options:

It automatically merges pull requests after an automated review.

It generates a prose summary and a bulleted list of key changes for pull requests.

It can validate the accuracy of the changes in the pull request.

It can answer questions about the changeset of the pull request.

Answer

B, D

Explanation

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

[Reference: GitHub Copilot Enterprise pull request review documentation.]

Questions # 10:

How does GitHub Copilot Chat ensure that a function works correctly?

Options:

By suggesting assertions based on the code's context and semantics.

By automatically writing all the tests for the function.

By writing the implementation code for the function.

By executing the test cases to validate the correctness of the code.

Answer

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.]

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