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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	How GitHub Copilot Works and Handles DataThis 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 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	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 6	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.

GitHub CopilotCertification Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
Where is the proxy service hosted?

A. Microsoft Azure
B. Amazon Web Service
C. Google Cloud Platform
D. Self hosted

Answer: A

Explanation:
The proxy service for GitHub Copilot is hosted on Microsoft Azure.

NEW QUESTION # 21
Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?

A. A tool solely designed for debugging and error correction.
B. A productivity tool that provides suggestions, but relying on human judgment.
C. A solution for software development, requiring no additional input or oversight.
D. A complete replacement for developers generating code.

Answer: B

Explanation:
GitHub Copilot Chat is designed to be a productivity enhancer, not a replacement for human developers. It provides suggestions and assists with coding tasks, but the final decision and validation always rest with the developer. Copilot Chat is meant to augment the developer's workflow, making it faster and more efficient, but it does not remove the need for human oversight and judgment.

NEW QUESTION # 22
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. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)
B. Code that contains logical errors or produces unexpected results
C. Code comments containing strong opinions or criticisms
D. Sexually suggestive or explicit content

Answer: A,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 # 23
Which Microsoft ethical AI principle is aimed at ensuring AI systems treat all people equally?

A. Reliability and Safety
B. Inclusiveness
C. Fairness
D. Privacy and Security

Answer: C

Explanation:
The principle of fairness ensures that AI systems treat all people equally and avoid discriminatory outcomes.

NEW QUESTION # 24
What is zero-shot prompting?

A. Only giving GitHub Copilot a question as a prompt and no examples
B. Telling GitHub Copilot it needs to show only the correct answer
C. Giving as little context to GitHub Copilot as possible
D. Giving GitHub Copilot examples of the problem you want to solve
E. Giving GitHub Copilot examples of the algorithm and outcome you want to use

Answer: A

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 # 25
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