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| Topic 1 | - 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 2 | - Testing with GitHub Copilot: This section of the exam measures skills of QA Engineers and Test Automation Specialists and covers AI-assisted testing methodologies, including the generation of unit tests, integration tests, and edge case detection. It explains how GitHub Copilot improves test effectiveness by suggesting relevant assertions and boilerplate test cases. The section also discusses privacy considerations, organizational code suggestion settings, and best practices for configuring GitHub Copilot’s testing features.
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| Topic 3 | - 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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| Topic 4 | - 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 5 | - 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 (Q119-Q124):
NEW QUESTION # 119
A large enterprise wants to enhance the code assistance support for their developers by incorporating internal code standards and best practices into GitHub Copilot. The IT team is also looking for scalable AI assistance with enterprise-level data management and governance. Which of the following plans can best accommodate this requirement?
- A. GitHub Copilot for Individual
- B. GitHub Copilot for Enterpriseright
- C. GitHub Copilot for Business
- D. GitHub Copilot Business for non-GitHub-hosted repositories
Answer: B
Explanation:
GitHub Copilot Enterprise includes support for private Knowledge Bases, which enables integration of internal documentation, best practices, and custom code snippets. It also supports enterprise-grade governance, security, and policy enforcement features-ideal for large organizations.
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 # 120
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?
- A. Code suggestions made by GitHub Copilot
- B. Accepted chat suggestions
- C. Changes to content exclusion settings
- D. Suggestions blocked by duplication detection filtering
Answer: C
Explanation:
Organization audit logs track changes to content exclusion settings, providing administrators with visibility into configuration changes.
NEW QUESTION # 121
How is GitHub Copilot Individual billed? (Each correct answer presents part of the solution.
Choose two.)
- A. Monthly, as a metered service based on actual consumption
- B. Free (not billed) for all open source projects
- C. Annually as a subscription
- D. Monthly as a subscription
Answer: C,D
Explanation:
GitHub Copilot Individual is billed as a monthly or annual subscription.
NEW QUESTION # 122
How can GitHub Copilot facilitate a smoother learning experience when diving into a new programming language? (Each correct answer presents part of the solution. Choose two.)
- A. GitHub Copilot Chat can provide guidance and support for common coding tasks and challenges in the targeted programming language.
- B. GitHub Copilot's /understand command will help GitHub Copilot to understand code written in a targeted programming language.
- C. GitHub Copilot can convert comments into code to grasp the syntax and nuances of a new programming language.
- D. GitHub Copilot can provide contextualized code suggestions and answer sources from an organization's documentation.
Answer: A,C
Explanation:
GitHub Copilot helps with learning new languages by providing guidance on common tasks and by converting comments into code, allowing developers to see syntax in action.
NEW QUESTION # 123
What are the potential risks associated with relying heavily on code generated from GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)
- A. GitHub Copilot may introduce security vulnerabilities by suggesting code with known exploits.
- B. GitHub Copilot may decrease developer velocity by requiring too much time in prompt engineering.
- C. GitHub Copilot may increase development lead time by providing irrelevant suggestions.
- D. GitHub Copilot's suggestions may not always reflect best practices or the latest coding standards.
Answer: A,D
Explanation:
Heavy reliance on GitHub Copilot can introduce security vulnerabilities if the generated code contains known exploits. Additionally, Copilot's suggestions may not always align with best practices or the latest standards, requiring careful review and validation.
NEW QUESTION # 124
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