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Microsoft GH-300 Exam Overview:

Certification Vendor:Microsoft / GitHub
Exam Name:GitHub Copilot Exam (GH-300)
Exam Number:GH-300
Exam Format:Drag and drop, Scenario-based questions, Multiple choice, Multiple response
Related Certifications:GitHub Copilot Fundamentals Part 1
GitHub Copilot Fundamentals Part 2
Real Exam Qty:60-75 (approximately 65 scored + unscored items)
Exam Price:USD 99
Available Languages:Portuguese (Brazil), Japanese, Spanish, Korean, English
Exam Duration:100-120
Passing Score:700/1000
Certificate Validity Period:2 years
Recommended Training:GitHub Copilot Fundamentals Part 2
GitHub Copilot Fundamentals Part 1
Exam Registration:Microsoft Learn Certification Page
Pearson VUE Scheduling
Sample Questions:Microsoft GH-300 Sample Questions
Exam Way:Online proctored (Pearson VUE) or test center
Pre Condition:Basic GitHub knowledge and experience using at least one programming language; familiarity with GitHub Copilot recommended but not strictly required
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-copilot/

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Microsoft GH-300 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 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.
Topic 5
  • 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 6
  • 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.

Microsoft GitHub Copilot Sample Questions (Q82-Q87):

NEW QUESTION # 82
In what ways can GitHub Copilot contribute to the design phase of the Software Development Life Cycle (SDLC)?

Answer: D

Explanation:
"Copilot can assist in the design phase by suggesting design patterns, frameworks, and best practices relevant to the context of your project." This shows Copilot contributes by offering design-related recommendations, not by independently producing full designs or managing collaboration.
References: GitHub Copilot use case documentation.


NEW QUESTION # 83
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.
Reference: GitHub Copilot Enterprise pricing and features.


NEW QUESTION # 84
When crafting prompts for GitHub Copilot, what is a recommended strategy to enhance the relevance of the generated code?

Answer: C

Explanation:
"To get the best results from GitHub Copilot, provide clear prompts and, when possible, include examples of expected input and output." This establishes that including examples is a recommended prompt engineering strategy.
References: GitHub Copilot prompt engineering documentation.


NEW QUESTION # 85
You have a GitHub Copilot subscription.
You need to start an interactive GitHub Copilot CLI session from the root folder of a project.
If you are NOT authenticated, GitHub Copilot must prompt you to sign in.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:


NEW QUESTION # 86
How does GitHub Copilot assist developers in minimizing context switching?

Answer: B

Explanation:
"Copilot reduces the need to switch between documentation, browsers, and editors by bringing suggestions and explanations directly into the IDE." This demonstrates that minimizing context switching comes from enabling developers to stay within their IDE.
References: GitHub Copilot productivity documentation.


NEW QUESTION # 87
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