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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	Privacy Fundamentals and Context Exclusions: This section of the exam measures skills of Cybersecurity Specialists and Compliance Officers and covers privacy safeguards and content exclusion settings in GitHub Copilot. It explains how Copilot can identify security vulnerabilities, suggest optimizations, and enforce secure coding practices. It also includes details on content ownership, data filtering mechanisms, and exclusion configurations. The section concludes with troubleshooting guidelines for managing context exclusions and ensuring compliance with organizational security policies.
Topic 3	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 4	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.
Topic 5	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.

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GitHub CopilotCertification Exam Sample Questions (Q40-Q45):

NEW QUESTION # 40
When can GitHub Copilot still use content that was excluded using content exclusion?

A. When the repository level settings allow overrides by the user.
B. If the contents of an excluded file are referenced in code that is not excluded, for example function calls.
C. If the content exclusion was configured at the enterprise level, and is overwritten at the organization level.
D. When the user prompts with @workspace.

Answer: B

Explanation:
GitHub Copilot can still use excluded content if it is referenced in code that is not excluded, such as function calls.

NEW QUESTION # 41
What types of prompts or code snippets might be flagged by the GitHub Copilot toxicity filter? (Each correct answer presents part of the solution. Choose two.)

A. Code comments containing strong opinions or criticisms
B. Code that contains logical errors or produces unexpected results
C. Sexually suggestive or explicit content
D. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)

Answer: C,D

Explanation:
GitHub Copilot includes a toxicity filter to prevent the generation of harmful or inappropriate content. This filter flags prompts or code snippets that contain hate speech, discriminatory language, or sexually suggestive or explicit content. This ensures a safe and respectful coding environment.

NEW QUESTION # 42
Which Copilot Individual features are available when using a supported extension for Visual Studio, VS Code, or JetBrains IDEs? (Each correct answer presents part of the solution. Choose two.)

A. Knowledge Base
B. Chat
C. Code suggestions
D. Pull Request Diff Analysis

Answer: B,C

Explanation:
GitHub Copilot Individual provides code suggestions and chat features when used with supported IDE extensions like Visual Studio, VS Code, and JetBrains IDEs.

NEW QUESTION # 43
Which of the following describes role prompting?

A. Giving GitHub Copilot multiple examples of the form of the data you want to use
B. Tell GitHub Copilot in what tone of voice it should respond
C. Prompt GitHub Copilot to explain what was the role of a suggestion
D. Describing in your prompt what your role is to get a better suggestion

Answer: D

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 # 44
How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?

A. It primarily relies on the model's training data to generate responses.
B. It uses user-provided documentation exclusively to generate responses.
C. It combines its training data set, code in user repositories, and external sources like Bing to generate responses.
D. It primarily uses search results from Bing to generate responses.

Answer: C

Explanation:
GitHub Copilot Chat combines its training data, code from user repositories, and external sources like Bing to generate comprehensive and relevant responses to coding questions.

NEW QUESTION # 45
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Valid GitHub-Copilot Learning Materials & Best GitHub-Copilot Study Material

GitHub GitHub-Copilot Exam Syllabus Topics:

GitHub - Authoritative Valid GitHub-Copilot Learning Materials

GitHub CopilotCertification Exam Sample Questions (Q40-Q45):

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