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Microsoft GH-300 Exam Overview:

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

Microsoft GitHub Copilot Sample Questions (Q33-Q38):

NEW QUESTION # 33
How can the insights gained from the metrics API be used to improve the development process in conjunction with GitHub Copilot?

Answer: A

Explanation:
"The Copilot metrics API provides insights into how suggestions are being accepted and used, enabling teams to analyze the relative impact of Copilot-generated code versus manually written code." This confirms option D is correct, as the API enables analysis of Copilot versus manual coding.
References: GitHub Copilot metrics API documentation.


NEW QUESTION # 34
GitHub Copilot in the Command Line Interface (CLI) can be used to configure the following settings: (Each correct answer presents part of the solution. Choose two.)

Answer: A,D

Explanation:
GitHub Copilot in the CLI allows configuration of settings such as the default execution confirmation and usage analytics. These settings help tailor the CLI experience to the user's preferences.
Reference: GitHub Copilot CLI configuration documentation.


NEW QUESTION # 35
How long does it take content exclusion to add or be updated?

Answer: A

Explanation:
Content exclusions typically take up to 30 minutes to be added or updated.
Reference: GitHub Copilot content exclusion documentation.


NEW QUESTION # 36
1.
blog.yatricloud.com
blog.yatricloud.com

Answer: B,D

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.
Reference: GitHub Copilot usage metrics API documentation.


NEW QUESTION # 37
What method can be used to interact with GitHub Copilot?

Answer: A

Explanation:
GitHub Copilot is an AI-powered code completion tool that integrates directly into supported Integrated Development Environments (IDEs) and code editors, such as Visual Studio Code, JetBrains IDEs, NeoVim, and others. Developers interact with it through their coding environment, where it provides real-time code suggestions, autocompletions, and (in some cases) chat-like capabilities via extensions or plugins (e.g., GitHub Copilot Chat in supported editors).
Evaluation of Options:
* A. By using a properly configured GitHub CLIThe GitHub CLI (Command Line Interface) is a tool for interacting with GitHub repositories and workflows from the terminal, but it is not a method for interacting with GitHub Copilot. Copilot operates within code editors/IDEs, not through the CLI.
Incorrect.
* B. By using chat capabilities in NeoVimThis is partially correct. GitHub Copilot can be used in NeoVim with the appropriate plugin (e.g., the Copilot.vim plugin), and GitHub Copilot Chat-a feature that allows conversational interaction-may also be available depending on the setup and version.
However, "chat capabilities in NeoVim" alone is not the primary or standard way to describe Copilot interaction, as it's more about code suggestions than chat. This is the closest option but not perfectly precise.Partially correct.
* C. From a watch window in an IDE debug sessionThe "watch window" in an IDE is used during debugging to monitor variable values, not to interact with GitHub Copilot. Copilot provides suggestions while coding, not specifically in debug sessions or watch windows.Incorrect.
* D. From a web browser athttps://github.copilot.comThere is no such URL as "https://github.copilot.
com" dedicated to interacting with GitHub Copilot. Copilot is accessed via GitHub's authentication and integrated into editors/IDEs, not through a standalone web browser interface. Information about Copilot is available on GitHub's official site (e.g.,https://github.com/features/copilot), but interaction happens in the coding environment.Incorrect.
Reference: GitHub Copilot interaction documentation.


NEW QUESTION # 38
......

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