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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	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 3	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.

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GitHub CopilotCertification Exam Sample Questions (Q78-Q83):

NEW QUESTION # 78
You are using GitHub Copilot under an Individual plan within Visual Studio Code. Which of the following is a core feature available to you under this plan?

A. Organization-wide policy settings and audit logs
B. Access to centralized Knowledge Bases across your company
C. Integration with GitHub Enterprise Server (GHE)
D. Context-aware code suggestions while typingright

Answer: D

Explanation:
GitHub Copilot Individual offers context-aware suggestions directly in the IDE, helping developers by predicting and completing code based on the current file and surrounding context.
Reference:
https://learn.microsoft.com/en-us/training/modules/introduction-to-github-Copilot/2-github-Copilot-your-ai-pair-programmer

NEW QUESTION # 79
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?

A. By using a specific command in the terminal.
B. By using specific prompt examples in your chat request.
C. By using a specific slash command in the prompt.
D. By using a specific setting in GitHub Copilot's configuration.

Answer: B

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 # 80
What are the potential limitations of GitHub Copilot in maintaining existing codebases?

A. GitHub Copilot can independently manage and resolve all merge conflicts in version control.
B. GitHub Copilot can refactor and optimize the entire codebase up to 10,000 lines of code.
C. GitHub Copilot might not fully understand the context and dependencies within a large codebase.
D. GitHub Copilot's suggestions are always aware of the entire codebase.

Answer: C

Explanation:
GitHub Copilot operates within a limited context window and may not capture all dependencies or the full project structure in a large codebase, so it can misunderstand context and require developer oversight.

NEW QUESTION # 81
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

A. Creation of a unit test scenario for newly developed Python code
B. Create a technical requirement specification from the business requirement documentation
C. Creation of end-to-end performance testing scenarios for a web application
D. Explain a legacy COBOL code and translate the code to another language like Python.

Answer: A,D

Explanation:
GitHub Copilot Chat is effective for explaining and translating legacy code and generating unit test scenarios for new code.

NEW QUESTION # 82
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?

A. GitHub Copilot can create and deploy full-stack applications based on a single query.
B. GitHub Copilot can suggest modern programming patterns based on your code.
C. GitHub Copilot can automatically refactor applications to align with upcoming standards.
D. GitHub Copilot can directly convert legacy applications into cloud-native architectures.

Answer: B

Explanation:
GitHub Copilot and GitHub Copilot Chat are powerful AI-driven tools designed to assist developers by providing context-aware code suggestions and interactive support. Specifically, in the context of modernizing applications, GitHub Copilot excels at analyzing existing code and suggesting modern programming patterns, best practices, and syntax improvements that align with contemporary development standards. For example, it can recommend updates to outdated constructs, propose more efficient algorithms, or suggest frameworks and libraries that are widely used in modern application development.

NEW QUESTION # 83
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