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GH-300 Authorized Pdf, Microsoft GH-300 Passed: GitHub Copilot Pass Certainly

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Microsoft GH-300 Exam Syllabus Topics:

Topic
Details

Topic 1

Domain 4: Prompt Crafting and Prompt Engineering This section measures skills of Software Developers and AI Interaction Designers in effectively crafting prompts to optimize Copilot’s output. It reviews foundational concepts such as prompt components, the role of language in prompting, zero-shot vs. few-shot prompting, and how chat history influences responses. Best practices and engineering principles for prompt design and training methods are also covered.

Topic 2

Responsible :This section of the exam measures skills of AI Ethics Officers and Risk Managers and covers the responsible and ethical usage of AI technologies. It explains the risks and limitations associated with generative AI tools, including biases in training data and the need to validate AI outputs. Candidates learn how to operate AI responsibly by identifying potential harms such as bias, fairness, privacy concerns, and mitigating these harms by applying ethical AI principles.

Topic 3

How GitHub Copilot Works and Handles Data: Designed for Machine Learning Engineers and Data Privacy Specialists, this section covers the data lifecycle and processing behind Copilot’s code suggestions. It explains how context is gathered, prompts constructed, responses generated, and post-processed through proxy services. Candidates understand Copilot’s data policies, handling of inputs, and limitations such as context window size and data age influencing suggestion relevance.

Topic 4

Privacy Fundamentals and Context Exclusions: This domain focuses on Security Engineers and Compliance Officers and addresses improving code quality with Copilot’s test suggestions and security optimizations. It covers identification of security vulnerabilities, performance enhancements, and privacy features like content exclusions at repository and organization levels with explanation of their limitations. Candidates learn about safeguarding mechanisms such as duplication detection, contractual protections, security checks, and troubleshooting guide for common Copilot issues including context exclusions and suggestion gaps.

Microsoft GitHub Copilot Sample Questions (Q29-Q34):

NEW QUESTION # 29
How can you get multiple suggestions from GitHub Copilot?

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

Answer: A

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

NEW QUESTION # 30
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

A. The Settings menu in the GitHub Mobile app.
B. The feedback section on the GitHub website.
C. By tweeting at GitHub's official X (previously known as Twitter) account.
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 # 31
Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?

A. A complete replacement for developers generating code.
B. A productivity tool that provides suggestions, but relying on human judgment.
C. A solution for software development, requiring no additional input or oversight.
D. A tool solely designed for debugging and error correction.

Answer: B

Explanation:
GitHub Copilot Chat is designed to be a productivity enhancer, not a replacement for human developers. It provides suggestions and assists with coding tasks, but the final decision and validation always rest with the developer. Copilot Chat is meant to augment the developer's workflow, making it faster and more efficient, but it does not remove the need for human oversight and judgment.

NEW QUESTION # 32
How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

A. It generates a prose summary and a bulleted list of key changes for pull requests.
B. It automatically merges pull requests after an automated review.
C. It can validate the accuracy of the changes in the pull request.
D. It can answer questions about the changeset of the pull request.

Answer: A,D

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

NEW QUESTION # 33
How can the concept of fairness be integrated into the process of operating an AI tool?

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

Answer: B

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 # 34
......

GitHub Copilot exam is one of the top-rated Microsoft GH-300 Exams. This GitHub Copilot exam offers an industrial-recognized way to validate a candidate's skills and knowledge. Everyone can participate in GitHub Copilot exam requirements after completing the GitHub Copilot exam. With the GitHub Copilot exam you can learn in-demand skills and upgrade your knowledge. You can enhance your salary package and you can get a promotion in your company instantly.

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