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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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.

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GitHub CopilotCertification Exam Sample Questions (Q88-Q93):

NEW QUESTION # 88
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.)

Answer: A,B

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 # 89
When using GitHub Copilot Chat to generate boilerplate code for various test types, how can you guide the AI to follow the testing standards of your company?

Answer: D

Explanation:
Providing concrete examples of your company's test structure and standards within the prompt steers Copilot Chat to generate boilerplate that aligns with your guidelines.


NEW QUESTION # 90
What is the process behind identifying public code matches when using a public code filter enabled in GitHub Copilot?

Answer: B

Explanation:
When the public code filter is enabled, GitHub Copilot runs code suggestions through filters designed to detect matches with publicly available code. This helps prevent the generation of code that might infringe on copyright or licensing agreements.


NEW QUESTION # 91
What is the correct sequence of steps to install GitHub Copilot CLI on a developer's system?

Answer: D

Explanation:
To install GitHub Copilot in the CLI, developers must first have the GitHub CLI (gh) installed.
Then, they run the correct command: gh extension install github/gh-Copilot. Authentication is completed with gh auth login. This sequence ensures the extension is installed properly and securely.
Reference:
https://docs.github.com/en/Copilot/managing-Copilot/configure-personal-settings/installing-github-Copilot-in-the-cli


NEW QUESTION # 92
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.)

Answer: C,D

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 # 93
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