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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 Price:USD 99
Passing Score:700/1000
Real Exam Qty:60-75 (approximately 65 scored + unscored items)
Certificate Validity Period:2 years
Related Certifications:GitHub Copilot Fundamentals Part 2
GitHub Copilot Fundamentals Part 1
Exam Duration:100-120
Available Languages:Korean, English, Portuguese (Brazil), Spanish, Japanese
Exam Format:Multiple response, Drag and drop, Scenario-based questions, Multiple choice
Recommended Training:GitHub Copilot Fundamentals Part 1
GitHub Copilot Fundamentals Part 2
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
  • 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
  • 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 4
  • 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 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.

Microsoft GitHub Copilot Sample Questions (Q108-Q113):

NEW QUESTION # 108
How does GitHub Copilot Chat help in understanding the existing codebase?

Answer: D

Explanation:
GitHub Copilot Chat helps in understanding existing codebases by answering questions about the code and generating explanations. This allows developers to quickly grasp the functionality and structure of unfamiliar code.
Reference: GitHub Copilot Chat documentation on code understanding.


NEW QUESTION # 109
How can users provide feedback about GitHub Copilot Chat using their IDE?

Answer: A

Explanation:
"In supported IDEs, you can provide feedback directly from the Copilot Chat panel by selecting the 'Share Feedback' option." This establishes that the in-IDE "Share Feedback" button is the official channel for submitting user feedback.
References: GitHub Copilot Chat feedback documentation.


NEW QUESTION # 110
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?

Answer: B

Explanation:
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.


NEW QUESTION # 111
You have a developer device named Device1 that runs macOS and has Homebrew installed.
Device1 will be used by a developer who has a GitHub Copilot plan.
You have a GitHub Enterprise Cloud enterprise account that has data residency at contoso.ghe.com.
You need to install the GitHub Copilot CLI on Device1 and start interactive authentication against the correct GitHub host.
Which two commands should you run in sequence?

Answer: B

Explanation:
Current GitHub Copilot documentation uses the standalone Copilot CLI installation and authentication flow.
On macOS with Homebrew, GitHub documents brew install --cask copilot-cli. For a GitHub Enterprise Cloud account with data residency, the CLI should authenticate directly against the enterprise host by using copilot login --host https://SUBDOMAIN.ghe.com; in this scenario that host is https://contoso.ghe.com. This is important because the Copilot license and authentication context must correspond to the GHE.com account that provides access. The PDF ' s selected commands reflect an older CLI flow and contain OCR or typing errors. For current GitHub Copilot Docs, the verified sequence is the Homebrew cask installation followed by copilot login --host https://contoso.ghe.com.


NEW QUESTION # 112
Which of the following are true about code suggestions? (Each correct answer presents part of the solution.
Choose two.)

Answer: B,D

Explanation:
Exact extracts:
* "You can accept individual words, lines, or entire suggestions with keyboard shortcuts." References: GitHub Copilot editor usage documentation.


NEW QUESTION # 113
......

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