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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
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	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	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 4	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.

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Free PDF 2026 GitHub GitHub-Copilot: GitHub CopilotCertification Exam –Trustable Latest Exam Format

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GitHub CopilotCertification Exam Sample Questions (Q88-Q93):

NEW QUESTION # 88
What is one of the recommended practices when using GitHub Copilot Chat to enhance code quality?

A. Rely solely on Copilot's suggestions without reviewing them.
B. Disable Copilot's inline suggestions.
C. Avoid using Copilot for complex tasks.
D. Regularly review and refactor the code suggested by Copilot.

Answer: D

Explanation:
Regularly reviewing and refactoring Copilot's output helps ensure that generated code adheres to your project's quality standards and catches any issues early.

NEW QUESTION # 89
What is the correct way to exclude specific files from being used by GitHub Copilot Business during code suggestions?

A. Use the GitHub Copilot settings in the user interface to exclude files.
B. Add the specific files to a copilot.ignore file.
C. Modify the .gitignore file to include the specific files.
D. Rename the files to include the suffix _no_copilot.

Answer: A

Explanation:
The correct way to exclude files is through the GitHub Copilot settings in the user interface, which allows administrators to specify files and directories to be ignored.

NEW QUESTION # 90
When using an IDE with a supported GitHub Copilot plug-in, which Chat features can be accessed from within the IDE? Each correct answer presents part of the solution. (Choose two.)

A. Generate unit tests
B. Plan coding tasks
C. Find out about releases and commits
D. Explain code and suggest improvements

Answer: A,D

Explanation:
Within your IDE's Copilot Chat pane you can ask it to explain existing code and suggest improvements.
You can also prompt it to generate unit tests for your code directly in the editor.

NEW QUESTION # 91
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?

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

Answer: C

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 # 92
Where is the proxy service hosted?

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

Answer: B

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

NEW QUESTION # 93
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