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| Topic | Details |
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| Topic 1 | - 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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| Topic 2 | - 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.
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| 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.
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| 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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| Topic 5 | - 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.
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GitHub CopilotCertification Exam Sample Questions (Q109-Q114):
NEW QUESTION # 109
Which GitHub Copilot plan could an Azure DevOps organization use without requiring a GitHub Enterprise license?
- A. Copilot Teams
- B. GitHub Copilot Individual
- C. GitHub Copilot Enterprise
- D. GitHub Copilot for Azure DevOps
Answer: D
Explanation:
The GitHub Copilot Business plan (branded for use with Azure DevOps) works on any DevOps platform - including Azure DevOps - without needing a GitHub Enterprise Cloud subscription. This lets organizations use Copilot's AI assistance in their existing Azure DevOps workflows without purchasing a GitHub Enterprise license.
NEW QUESTION # 110
How long does GitHub retain Copilot data for Business and Enterprise? (Each correct answer presents part of the solution. Choose two.)
- A. User Engagement Data: Kept for One Year
- B. User Engagement Data: Kept for Two Years
- C. Prompts and Suggestions: Retained for 28 days
- D. Prompts and Suggestions: Not retained
Answer: B,C
Explanation:
For GitHub Copilot Business and Enterprise, prompts and suggestions are retained for 28 days to provide context and improve the service. User engagement data, which includes usage patterns and interactions, is kept for two years. This data retention policy is designed to balance service improvement with user privacy.
NEW QUESTION # 111
A developer is working for an enterprise that hosts all its code on Bitbucket and wants to leverage GitHub Copilot. However, their organization doesn't have any GitHub repositories. Can they still access GitHub Copilot?
- A. No, GitHub Copilot for CLI can only work with GitHub-hosted projects
- B. Yes, only when the organization migrates their Codebase to GitHub from Bitbucket
- C. No, Copilot can only be used with GitHub repositories
- D. Yes, by using GitHub Copilot for business, they can integrate GitHub Copilot with non-GitHub- hosted repositoriesright
Answer: D
Explanation:
GitHub Copilot Business supports usage with non-GitHub repositories. Developers can use Copilot in supported IDEs regardless of the repository hosting platform, enabling access to AI coding suggestions even if code is hosted outside GitHub.
Reference:
https://learn.microsoft.com/en-us/training/modules/github-Copilot-management-and-customizations/2-explore-github-Copilot-plans-associated-management-customization- features?ns-enrollment-type=learningpath&ns-enrollment-id=learn.github-Copilot
NEW QUESTION # 112
Which scenarios can GitHub Copilot Chat be used to increase productivity? Each correct answer presents part of the solution. (Choose two.)
- A. A project plan for the team needs to be generated using a project management software.
- B. A developer is added to a new project and would like to understand the current software code.
- C. Fast tracking of release management activities to move code to production main branch.
- D. Create a documentation file for the newly created code base.
Answer: B,D
Explanation:
GitHub CopilotꢀChat can draft documentation directly from your code's structure and comments, and it can walk a new team member through existing code by summarizing and explaining its components, thereby boosting onboarding efficiency and overall productivity.
NEW QUESTION # 113
A social media manager wants to use AI to filter content. How can they promote transparency in the platform's AI operations?
- A. By relying on a well-regarded AI development company.
- B. By providing clear explanations about the types of content the AI is designed to filter and how it arrives at its conclusion.
- C. By regularly updating the AI filtering algorithm.
- D. By focusing on user satisfaction with the content filtering
Answer: B
Explanation:
Offering clear, accessible explanations of what content the AI filters and the rationale behind its decisions ensures users understand and trust the system's operation, embodying the transparency principle in ethical AI.
NEW QUESTION # 114
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