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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:	GitHub
Exam Name:	Microsoft GitHub Copilot
Exam Number:	GH-300
Exam Format:	Multiple Choice
Exam Price:	$99 USD
Certificate Validity Period:	2 years
Related Certifications:	GitHub Copilot Certified Professional
Available Languages:	English
Passing Score:	700 / 1000
Exam Duration:	100 minutes
Real Exam Qty:	60-65
Sample Questions:	GitHub GitHub-Copilot Sample Questions
Exam Way:	Proctored (Online or Offline Test Centers)
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/github-copilot

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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
Topic 1	Testing with GitHub Copilot: This section of the exam measures skills of QA Engineers and Test Automation Specialists and covers AI-assisted testing methodologies, including the generation of unit tests, integration tests, and edge case detection. It explains how GitHub Copilot improves test effectiveness by suggesting relevant assertions and boilerplate test cases. The section also discusses privacy considerations, organizational code suggestion settings, and best practices for configuring GitHub Copilot’s testing features.
Topic 2	How GitHub Copilot Works and Handles Data: This section of the exam measures the skills of Data Security Specialists and DevOps Engineers and covers how GitHub Copilot processes data, handles code suggestions and manages privacy concerns. It explains the data pipeline for Copilot’s suggestions, how it gathers context, and how prompts are processed through its AI model. The section also discusses the limitations of AI-generated code, the effects of historical data on suggestions, and the role of prompt crafting. Best practices for improving prompt effectiveness and optimizing AI-generated responses are included.
Topic 3	Developer Use Cases for AI: This section of the exam measures skills of Full-Stack Developers and Cloud Engineers and covers how AI enhances developer productivity across various tasks such as learning new programming languages, debugging, writing documentation, and refactoring code. It discusses how GitHub Copilot integrates with the Software Development Lifecycle (SDLC) and its role in modernizing legacy applications. It also highlights the use of AI for personalized responses, sample data generation, and improving overall efficiency in software development.
Topic 4	Prompt Engineering: This section of the exam measures skills of AI Engineers and Software Developers and covers the fundamentals of prompt engineering, including key principles, techniques, and best practices for generating high-quality outputs. It explains different prompting strategies such as zero-shot and few-shot prompting, how context influences AI-generated responses, and the role of structured prompts in guiding Copilot's behavior. It also discusses the prompt lifecycle and ways to enhance model performance through refined input instructions.
Topic 5	Responsible AI: This section of the exam measures the skills of AI Ethics Analysts and AI Developers and covers the principles of responsible AI usage, the risks associated with AI, and the limitations of generative AI tools. It includes the importance of validating AI-generated outputs and operating AI systems responsibly. It also explores potential harms such as bias, privacy concerns, and fairness issues, along with methods to mitigate these risks. The ethical considerations of AI development and deployment are also discussed.
Topic 6	GitHub Copilot Plans and FeaturesThis section of the exam measures the skills of Software Engineers and IT Administrators and covers different GitHub Copilot plans, including Individual, Business, and Enterprise editions. It explains the integration of GitHub Copilot within IDEs and discusses key features such as inline chat, multiple suggestions, and exception handling. The section details the policies for managing GitHub Copilot within organizations, including auditing logs and API management. It also highlights advanced functionalities like knowledge bases for improved code quality and best practices for Copilot Chat usage.

GitHub CopilotCertification Exam Sample Questions (Q72-Q77):

NEW QUESTION # 72
How long does it take content exclusion to add or be updated?

A. 45 - 60 minutes
B. 60 - 90 minutes
C. Up to 30 minutes
D. 24 hours

Answer: C

Explanation:
Content exclusions typically take up to 30 minutes to be added or updated.

NEW QUESTION # 73
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.)

A. The default execution confirmation
B. The default editor
C. GitHub CLI subcommands
D. Usage analytics

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.

NEW QUESTION # 74
How does GitHub Copilot Chat ensure that a function works correctly?

A. By writing the implementation code for the function.
B. By automatically writing all the tests for the function.
C. By suggesting assertions based on the code's context and semantics.
D. By executing the test cases to validate the correctness of the code.

Answer: C

Explanation:
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.

NEW QUESTION # 75
What is the correct way to access the audit log events for GitHub Copilot Business?

A. Use the Audit log section in the organization's GitHub settings
B. Navigate to the Insights tab in the repository settings
C. Use the Code tab in the GitHub repository
D. Navigate to the Security tab in the organization's GitHub settings

Answer: A

Explanation:
Audit log events for GitHub Copilot Business can be accessed through the Audit log section within the organization's GitHub settings. This log provides a record of activities related to Copilot usage and configuration.

NEW QUESTION # 76
How can you improve the context used by GitHub Copilot? (Each correct answer presents part of the solution.
Choose two.)

A. By adding relevant code snippets to your prompt
B. By adding the important files to your .gitconfig
C. By adding the full file paths to your prompt of important files
D. By opening the relevant tabs in your IDE

Answer: A,D

Explanation:
Improving the context for GitHub Copilot involves opening relevant files in your IDE to provide immediate context and adding relevant code snippets directly to your prompts to give Copilot specific examples and information.

NEW QUESTION # 77
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