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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)
Available Languages:Korean, Japanese, Portuguese (Brazil), Spanish, English
Exam Duration:100-120
Related Certifications:GitHub Copilot Fundamentals Part 2
GitHub Copilot Fundamentals Part 1
Certificate Validity Period:2 years
Exam Price:USD 99
Passing Score:700/1000
Exam Format:Drag and drop, Scenario-based questions, Multiple response, Multiple choice
Recommended Training:GitHub Copilot Fundamentals Part 2
GitHub Copilot Fundamentals Part 1
Exam Registration:Pearson VUE Scheduling
Microsoft Learn Certification Page
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
  • 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 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
  • 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 4
  • 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 5
  • 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 6
  • 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.

Microsoft GitHub Copilot Sample Questions (Q60-Q65):

NEW QUESTION # 60
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)

Answer: D,E

Explanation:
You can use GitHub Copilot for inline refactoring suggestions by adding comments to your code to trigger suggestions and by highlighting the code and selecting "Refactor using GitHub Copilot" from the context menu.
Reference: GitHub Copilot refactoring documentation.


NEW QUESTION # 61
What is zero-shot prompting?

Answer: D

Explanation:
Zero-shot prompting involves asking GitHub Copilot a question or giving a task without providing any examples. This relies on the model's pre-existing knowledge to generate a response.


NEW QUESTION # 62
How does GitHub Copilot Chat help to fix security issues in your codebase?

Answer: A

Explanation:
"When Copilot Chat generates suggestions, it may annotate them with warnings about known insecure patterns, helping developers identify potential vulnerabilities in context." This indicates that Copilot Chat assists with security by annotating code suggestions with vulnerability patterns.
References: GitHub Copilot Chat security and responsible use documentation.


NEW QUESTION # 63
A company is currently storing code in Bitbucket and would like to use GitHub Copilot. Which GitHub Copilot plan will be most cost effective to allow them to manage users with their Identity Provider (e.g. Okta)?

Answer: C

Explanation:
GitHub Copilot Enterprise is the most cost-effective plan for managing users with an Identity Provider like Okta, as it provides enterprise-level features and integration.


NEW QUESTION # 64
When using GitHub Copilot Chat to generate unit tests, which slash command would you use?

Answer: C


NEW QUESTION # 65
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