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Microsoft GH-300 Exam Overview:

Certification Vendor:	Microsoft / GitHub
Exam Name:	GitHub Copilot Exam (GH-300)
Exam Number:	GH-300
Available Languages:	Japanese, Portuguese (Brazil), English, Spanish, Korean
Exam Duration:	100-120
Real Exam Qty:	60-75 (approximately 65 scored + unscored items)
Exam Price:	USD 99
Certificate Validity Period:	2 years
Passing Score:	700/1000
Exam Format:	Drag and drop, Scenario-based questions, Multiple response, Multiple choice
Related Certifications:	GitHub Copilot Fundamentals Part 1 GitHub Copilot Fundamentals Part 2
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:

Topic	Details
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	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 3	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.

Microsoft GitHub Copilot Sample Questions (Q58-Q63):

NEW QUESTION # 58
In what ways can GitHub Copilot contribute to the design phase of the Software Development Life Cycle (SDLC)?

A. GitHub Copilot can suggest design patterns and best practices relevant to the project.
B. GitHub Copilot can generate user interface (UI) prototypes without prompting.
C. GitHub Copilot can independently create a complete software design.
D. GitHub Copilot can manage design team collaboration and version control.

Answer: A

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 # 59
How can GitHub Copilot assist with code refactoring tasks?

A. GitHub Copilot can automatically rewrite code to follow best practices.
B. GitHub Copilot can remove unnecessary files from the project directory.
C. GitHub Copilot can fix syntax errors without user input.
D. GitHub Copilot can suggest refactoring improvements for better code quality.

Answer: D

Explanation:
GitHub Copilot can analyze existing code and suggest refactoring improvements to enhance code quality, readability, and maintainability. It can propose changes to improve code structure, reduce complexity, and follow best practices.

NEW QUESTION # 60
Why is code reviewing still necessary when using GitHub Copilot to write tests?

A. Because GitHub Copilot generates the best code possible for the test scenario.
B. Because GitHub Copilot's generated test cases may not cover all possible scenarios.
C. Because GitHub Copilot replaces the need for manual testing.
D. Because GitHub Copilot can cover all possible scenarios in your test cases.

Answer: B

Explanation:
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.
Reference: GitHub Copilot testing best practices.

NEW QUESTION # 61
effectiveness of GitHub Copilot? (Each correct answer presents part of the solution. Choose two.) 1
1.
blog.yatricloud.com
blog.yatricloud.com

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

Answer: B,E

Explanation:
The GitHub Copilot usage metrics API provides insights into the acceptance rate of code suggestions and Copilot Chat specific suggestions acceptance metrics, helping organizations evaluate its effectiveness.

NEW QUESTION # 62
What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution.
Choose two.)

A. No biases in code suggestions
B. Extensive support for all programming languages
C. Ability to handle complex code structures
D. Limited training data

Answer: C,D

Explanation:
Exact extracts:
* "GitHub Copilot Chat, like all AI models, is limited by its training data and may not always provide accurate or up-to-date answers." References: GitHub Copilot Chat limitations documentation.

NEW QUESTION # 63
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