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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilot’s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilot’s impact is also included.
Topic 5
  • Domain 6: Testing with GitHub Copilot: This section measures abilities of QA Engineers and Test Automation Specialists to use Copilot for test generation, including unit and integration tests. It explains how Copilot can identify edge cases and assist in writing assertions. The domain also covers different Copilot subscription SKUs, privacy considerations, organizational code suggestion settings, and configuration files related to Copilot.
Topic 6
  • 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.

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Microsoft GitHub Copilot Sample Questions (Q127-Q132):

NEW QUESTION # 127
When using GitHub Copilot Chat to generate unit tests, which slash command would you use?

Answer: C


NEW QUESTION # 128
What can be done during AI development to minimize bias?

Answer: C

Explanation:
"Minimizing bias requires diverse datasets, use of fairness metrics, and human oversight throughout development and deployment." This clearly confirms that the proper approach is a combination of diverse data, fairness metrics, and oversight.
References: Microsoft Responsible AI and GitHub Copilot fairness guidelines.


NEW QUESTION # 129
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?

Answer: D

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 # 130
How can GitHub Copilot be limited when it comes to suggesting unit tests?

Answer: C

Explanation:
GitHub Copilot often suggests basic unit tests and may not cover all edge cases or complex integration scenarios, requiring developers to supplement its suggestions.
Reference: GitHub Copilot testing limitations.


NEW QUESTION # 131
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)

Answer: A,B

Explanation:
You can use GitHub Copilot for inline refactoring suggestions by adding comments to your code to trigger suggestions and by highlighting the code and selecting " Refactor using GitHub Copilot " from the context menu.
Reference: GitHub Copilot refactoring documentation.


NEW QUESTION # 132
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