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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
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 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 6
  • 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.

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Microsoft GitHub Copilot Sample Questions (Q121-Q126):

NEW QUESTION # 121
Which scenarios can GitHub Copilot Chat be used to increase productivity? (Each correct answer presents part of the solution. Choose two.)

Answer: A,B

Explanation:
Exact extracts:
* "Copilot Chat can generate documentation based on your code."
References: GitHub Copilot Chat productivity documentation.


NEW QUESTION # 122
How does GitHub Copilot suggest code optimizations for improved performance?

Answer: C

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 # 123
Which GitHub Copilot pricing plans include features that exclude your GitHub Copilot data like usage, prompts, and suggestions from default training GitHub Copilot? (Choose two correct answers.)

Answer: B,C

Explanation:
"For Copilot Business and Copilot Enterprise, user data such as code suggestions, prompts, and completions are excluded from training GitHub Copilot's models." This confirms that only Business and Enterprise plans provide this exclusion feature.
References: GitHub Copilot data usage and privacy documentation.


NEW QUESTION # 124
How do you generate code suggestions with GitHub Copilot in the CLI?

Answer: C

Explanation:
"To generate a suggestion, run gh copilot suggest, provide your command description, then review and select from the suggestions returned." This confirms the CLI command flow in option C.
References: GitHub Copilot CLI documentation.


NEW QUESTION # 125
Which of the following does GitHub Copilot's LLM derive context from when producing a response?

Answer: B

Explanation:
"Copilot may use context from neighboring or related files in the project to improve the accuracy of its suggestions." This confirms that context is enriched with information from related files, making option C correct.
References: GitHub Copilot context derivation documentation.


NEW QUESTION # 126
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