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Microsoft GH-300 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GitHub Copilot
Exam Number:GH-300
Passing Score:700 / 1000
Exam Price:$99 USD
Available Languages:French, Arabic (Saudi Arabia), Chinese (Simplified), Portuguese (Brazil), Korean, Japanese, German, Spanish, English
Exam Format:Proctored, Scenario-based, Multiple-choice
Real Exam Qty:60–65
Certificate Validity Period:1 year
Exam Duration:100 minutes
Recommended Training:Microsoft Learn: GitHub Copilot Learning Path
Exam Registration:Microsoft Learn Exam Details
Pearson VUE Registration
Sample Questions:Microsoft GH-300 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:Basic familiarity with GitHub, software development workflows, and at least one programming language; no formal prerequisites required
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300

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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
  • 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
  • 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.
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 (Q68-Q73):

NEW QUESTION # 68
What is the best way to share feedback about GitHub Copilot Chat when using it on GitHub Mobile?

Answer: A

Explanation:
"On GitHub Mobile, you can use emojis in the Copilot Chat interface to provide quick feedback on the responses." This makes option A correct.
References: GitHub Copilot Mobile documentation.


NEW QUESTION # 69
What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution.
Choose two.)

Answer: B,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 # 70
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?

Answer: A

Explanation:
"The quality of Copilot Chat responses depends on the clarity and specificity of your prompts. You can guide Copilot to follow organizational standards by including examples or requirements in your request." This means prompt engineering with specific examples is the way to align with company standards.
References: GitHub Copilot Chat best practices documentation.


NEW QUESTION # 71
Which of the following is correct about GitHub Copilot Knowledge Bases?

Answer: C

Explanation:
GitHub Copilot Knowledge Bases is an Enterprise feature that allows the tool to use an organization's internal documentation and code for more accurate and relevant suggestions.


NEW QUESTION # 72
Which of the following describes role prompting?

Answer: C

Explanation:
Role prompting involves explicitly stating your role or the persona you want GitHub Copilot to adopt within your prompt. This helps Copilot provide more contextually relevant and accurate suggestions. By defining your role (e.g., "As a senior software engineer," "As a technical writer"), you guide Copilot to tailor its responses to align with the expertise and perspective associated with that role. This improves the quality and relevance of the generated code and explanations.


NEW QUESTION # 73
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