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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
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
  • 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.
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
  • 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.

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Microsoft GitHub Copilot Sample Questions (Q49-Q54):

NEW QUESTION # 49
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?

Answer: B

Explanation:
Organization audit logs track changes to content exclusion settings, providing administrators with visibility into configuration changes.
Reference: GitHub Copilot Business audit logs.


NEW QUESTION # 50
How does GitHub Copilot suggest code optimizations for improved performance?

Answer: B

Explanation:
GitHub Copilot suggests code optimizations by analyzing the codebase and recommending more efficient algorithms or data structures.
Reference: GitHub Copilot code optimization documentation.


NEW QUESTION # 51
Which GitHub Copilot plan allows for prompt and suggestion collection?

Answer: D

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.


NEW QUESTION # 52
Which of the following describes role prompting?

Answer: D

Explanation:
Role prompting involves explicitly stating your role or the persona you want GitHub Copilot to adopt within your prompt. This helps Copilot provide more contextually relevant and accurate suggestions. By defining your role (e.g., "As a senior software engineer," "As a technical writer"), you guide Copilot to tailor its responses to align with the expertise and perspective associated with that role. This improves the quality and relevance of the generated code and explanations.
Reference: GitHub Copilot documentation on prompt engineering and best practices.


NEW QUESTION # 53
What GitHub Copilot pricing plan gives you access to your company's knowledge bases?

Answer: C

Explanation:
GitHub Copilot Enterprise provides access to your company's knowledge bases, enabling the tool to provide contextually relevant suggestions based on your organization's specific documentation and code.


NEW QUESTION # 54
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