GITHUB COPILOTCERTIFICATION EXAM FREE PDF DUMPS & GITHUB-COPILOT LATEST STUDY VCE & GITHUB COPILOTCERTIFICATION EXAM TEST ENGINE TORRENT

GitHub CopilotCertification Exam free pdf dumps & GitHub-Copilot latest study vce & GitHub CopilotCertification Exam test engine torrent

GitHub CopilotCertification Exam free pdf dumps & GitHub-Copilot latest study vce & GitHub CopilotCertification Exam test engine torrent

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Tags: Valid GitHub-Copilot Exam Discount, GitHub-Copilot Authorized Certification, Answers GitHub-Copilot Real Questions, GitHub-Copilot Valid Exam Vce Free, GitHub-Copilot Reliable Braindumps Sheet

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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 4
  • 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 5
  • 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 6
  • 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.

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GitHub CopilotCertification Exam Sample Questions (Q45-Q50):

NEW QUESTION # 45
How can GitHub Copilot assist developers during the requirements analysis phase of the Software Development Life Cycle (SDLC)?

  • A. By automatically generating detailed requirements documents.
  • B. By providing templates and code snippets that help in documenting requirements.
  • C. By managing stakeholder communication and meetings.
  • D. By identifying and fixing potential requirement conflicts when using /help.

Answer: B

Explanation:
GitHub Copilot can assist during the requirements analysis phase by providing templates and code snippets that aid in documenting requirements. This helps streamline the process of capturing and organizing project requirements.


NEW QUESTION # 46
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

  • A. Creation of a unit test scenario for newly developed Python code
  • B. Explain a legacy COBOL code and translate the code to another language like Python.
  • C. Creation of end-to-end performance testing scenarios for a web application
  • D. Create a technical requirement specification from the business requirement documentation

Answer: A,B

Explanation:
GitHub Copilot Chat is effective for explaining and translating legacy code and generating unit test scenarios for new code.


NEW QUESTION # 47
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 collecting large datasets for training will ensure fairness.
  • C. Focusing on accessibility 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 # 48
How can you get multiple suggestions from GitHub Copilot?

  • A. By opening the completions panel in your editor
  • B. By using the inline chat functionality with the command 'multiple'
  • C. By asking for multiple suggestions using comments in your code
  • D. By using @workspace in the chat window

Answer: A

Explanation:
You can get multiple suggestions by opening the completions panel in your editor, which displays alternative code suggestions.


NEW QUESTION # 49
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

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

Answer: B

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 # 50
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