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Microsoft GitHub Administrator GH-300

GH-300

Exam Code: GH-300

Exam Name: GitHub Copilot

Updated: Nov 04, 2026

Q & A: 131 Questions and Answers

GH-300 Free Demo download:

PDF Version Test Engine Online Test Engine

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About Microsoft GH-300 Exam

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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
  • 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 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.
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.

Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300

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Microsoft GitHub Copilot Sample Questions:

Question #1
What kind of insights can the GitHub Copilot usage metrics API provide to help evaluate the effectiveness of GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

A. The API can refactor your code to improve productivity.
B. The API can provide Copilot Chat specific suggestions acceptance metrics.
C. The API can generate detailed reports on code quality improvements made by GitHub Copilot.
D. The API can track the number of code suggestions accepted and used in the organization.
E. The API can provide feedback on coding style and standards compliance.


Question #2
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 answer questions about the changeset of the pull request.
D. It can validate the accuracy of the changes in the pull request.


Question #3
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?

A. GitHub Copilot can refactor applications to align with upcoming standards.
B. GitHub Copilot can create and deploy full-stack applications based on a single query.
C. GitHub Copilot can suggest modern programming patterns based on your code.
D. GitHub Copilot can directly convert legacy applications into cloud-native architectures.


Question #4
How can GitHub Copilot aid developers in writing documentation for their code?

A. GitHub Copilot can suggest summaries or descriptions based on the code ' s functionality.
B. GitHub Copilot cannot assist in writing documentation or comments.
C. GitHub Copilot can only generate content in markdown format.
D. GitHub Copilot can automatically generate complete and detailed documentation.


Question #5
When using GitHub Copilot Chat to generate boilerplate code for various test types, how can you guide the AI to follow the testing standards of your company?

A. By using a specific setting in GitHub Copilot ' s configuration.
B. By using a specific command in the terminal.
C. By using specific prompt examples in your chat request.
D. By using a specific slash command in the prompt.


Solutions:

Question #1
Correct Answer: B,D
Question #2
Correct Answer: A,C
Question #3
Correct Answer: C
Question #4
Correct Answer: A
Question #5
Correct Answer: C

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