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GitHub GitHub-Copilot Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Improve Developer Productivity10-15%- Agent workflows, productivity, SDLC integration
Topic 2: Configure Privacy, Exclusions, Safeguards10-15%- Agent permissions, content exclusions, org policies
Topic 3: Apply Prompt Engineering and Context10-15%- Model-specific prompting, context files, best practices
Topic 4: Understand GitHub Copilot Data and Architecture10-15%- Pipeline, MCP, context gathering, data handling
Topic 5: Responsible AI15-20%- Ethics, validation, bias mitigation, transparency
Topic 6: GitHub Copilot Features25-30%- Multi-model, Agent Mode, Mission Control, BYOK

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GitHub CopilotCertification Exam Sample Questions (Q98-Q103):

NEW QUESTION # 98
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: C

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 # 99
How does GitHub Copilot assist developers in reducing the amount of manual boilerplate code they write?

Answer: C

Explanation:
GitHub Copilot identifies repetitive patterns and offers ready‑to‑use code snippets - such as class definitions, CRUD operations, or setup routines - so you don't have to write the same boilerplate from scratch.


NEW QUESTION # 100
As a developer who is evaluating the efficiency of GitHub Copilot in generating accurate code across different problem domains. During your R&D, you want to consider the limitations of GenAI tools like Copilot. Which of the following options best describes a core limitation?

Answer: B

Explanation:
Copilot is trained on a vast amount of data, which is publicly available; this data may include the biased, outdated, or incorrect practices of code implementation. This typically highlights a key concern in Responsible AI.
References:
https://learn.microsoft.com/en-us/training/modules/responsible-ai-with-github-Copilot/2-manage-ai-risks


NEW QUESTION # 101
What role does chat history play in GitHub Copilot's code suggestions?

Answer: D

Explanation:
Chat history provides valuable context to GitHub Copilot, helping it generate more relevant and accurate code suggestions based on previous interactions and conversations.


NEW QUESTION # 102
Which of the following steps correctly demonstrates how to establish an organization-wide policy for GitHub Copilot Business to restrict its use to certain repositories?

Answer: C

Explanation:
Organization-wide Copilot Business policies are set up in your GitHub organization's settings, where you can specify exactly which repositories are allowed or blocked for Copilot access.


NEW QUESTION # 103
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