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Microsoft GH-300 Exam Overview:

Certification Vendor:Microsoft
Exam Name:GitHub Copilot
Exam Number:GH-300
Real Exam Qty:65
Available Languages:English, Korean, Spanish, Portuguese (Brazil), Japanese
Related Certifications:GitHub Foundations
GitHub Actions
Passing Score:700 / 1000
Exam Format:Multiple-choice, Scenario-based
Certificate Validity Period:1 year (renewable)
Exam Price:$99 USD
Exam Duration:100 minutes
Sample Questions:Microsoft GH-300 Sample Questions
Exam Way:Online proctored exam (Pearson VUE)
Pre Condition:No formal prerequisites. Microsoft recommends practical experience using GitHub Copilot in an IDE and a general understanding of software development principles.
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
  • 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 3
  • 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 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
  • 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 6
  • 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 (Q109-Q114):

NEW QUESTION # 109
When can GitHub Copilot still use content that was excluded using content exclusion?

Answer: C

Explanation:
"If excluded content is referenced by non-excluded code, such as through function calls, Copilot may still use that reference context." This confirms that excluded content can indirectly appear if referenced elsewhere.
References: GitHub Copilot content exclusions limitations documentation.


NEW QUESTION # 110
What practices enhance the quality of suggestions provided by GitHub Copilot? (Select three.)

Answer: A,C,E

Explanation:
The quality of Copilot's suggestions is enhanced by clearly defining the task, using meaningful variable names, and providing examples of the desired output.


NEW QUESTION # 111
Which of the following statements best describes the impact of GitHub Copilot on the software development process?

Answer: C

Explanation:
GitHub Copilot primarily impacts the software development process by increasing productivity through automating repetitive coding tasks.


NEW QUESTION # 112
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: C,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 # 113
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 # 114
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