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Latest GitHub-Copilot Exam Price - Exam GitHub-Copilot Tutorial

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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

Prompt Engineering: This section of the exam measures skills of AI Engineers and Software Developers and covers the fundamentals of prompt engineering, including key principles, techniques, and best practices for generating high-quality outputs. It explains different prompting strategies such as zero-shot and few-shot prompting, how context influences AI-generated responses, and the role of structured prompts in guiding Copilot's behavior. It also discusses the prompt lifecycle and ways to enhance model performance through refined input instructions.

Topic 3

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 4

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.

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Exam GitHub-Copilot Tutorial | GitHub-Copilot Practice Questions

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GitHub CopilotCertification Exam Sample Questions (Q45-Q50):

NEW QUESTION # 45
How can GitHub Copilot facilitate a smoother learning experience when diving into a new programming language? (Each correct answer presents part of the solution. Choose two.)

A. GitHub Copilot Chat can provide guidance and support for common coding tasks and challenges in the targeted programming language.
B. GitHub Copilot can convert comments into code to grasp the syntax and nuances of a new programming language.
C. GitHub Copilot's /understand command will help GitHub Copilot to understand code written in a targeted programming language.
D. GitHub Copilot can provide contextualized code suggestions and answer sources from an organization's documentation.

Answer: A,B

Explanation:
GitHub Copilot helps with learning new languages by providing guidance on common tasks and by converting comments into code, allowing developers to see syntax in action.

NEW QUESTION # 46
What content can be configured to be excluded with content exclusions? (Each correct answer presents part of the solution. Choose three.)

A. Folders
B. Repositories
C. Lines in files
D. Gists
E. Files

Answer: A,B,E

Explanation:
Content exclusions allow you to exclude files, folders, and repositories from being used by GitHub Copilot.

NEW QUESTION # 47
What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution.
Choose two.)

A. No biases in code suggestions
B. Ability to handle complex code structures
C. Limited training data
D. Extensive support for all programming languages

Answer: C,D

Explanation:
GitHub Copilot Chat has limitations such as limited training data, which can affect the accuracy of its suggestions, and it does not provide extensive support for all programming languages.

NEW QUESTION # 48
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

A. By tweeting at GitHub's official X (previously known as Twitter) account.
B. The Settings menu in the GitHub Mobile app.
C. The feedback section on the GitHub website.
D. Use the emojis in the Copilot Chat interface.

Answer: D

Explanation:
The best way to share feedback on GitHub Mobile is using the emojis in the Copilot Chat interface, which allows for direct and immediate feedback.

NEW QUESTION # 49
Why is code reviewing still necessary when using GitHub Copilot to write tests?

A. Because GitHub Copilot's generated test cases may not cover all possible scenarios.
B. Because GitHub Copilot generates the best code possible for the test scenario.
C. Because GitHub Copilot replaces the need for manual testing.
D. Because GitHub Copilot can cover all possible scenarios in your test cases.

Answer: A

Explanation:
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.

NEW QUESTION # 50
......

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