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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic	Details
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.
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.
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.
Topic 4	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 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 (Q59-Q64):

NEW QUESTION # 59
Select a strategy to increase the performance of GitHub Copilot Chat.

A. Optimize the usage of memory-intensive operations within generated code
B. Use a single GitHub Copilot Chat query to find resolutions for the collection of technical requirements
C. Limit the number of concurrent users accessing GitHub Copilot Chat
D. Apply prompt engineering techniques to be more specific

Answer: D

Explanation:
Applying prompt engineering techniques to be more specific is the best strategy to increase the performance and relevance of GitHub Copilot Chat's responses.

NEW QUESTION # 60
What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution.
Choose two.)

A. No biases in code suggestions
B. Limited training data
C. Ability to handle complex code structures
D. Extensive support for all programming languages

Answer: B,D

Explanation:
GitHub Copilot Chat has limitations such as limited training data, which can affect the accuracy of its suggestions, and it does not provide extensive support for all programming languages.

NEW QUESTION # 61
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 # 62
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?

A. Suggest innovative coding solutions that are not yet popular.
B. Suggest code snippets that reflect the most common practices in the training data.
C. Suggest completely novel projects, while reducing time on a project.
D. Suggest homogeneous solutions if provided a diverse data set.

Answer: B

Explanation:
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.

NEW QUESTION # 63
What is the primary role of the /optimize slash command in Visual Studio?

A. Translates code into a more performant language.
B. Automatically formats the code according to the selected style guide.
C. Summarizes your documentation into more maintainable and readable formats.
D. Enhances the performance of the selected code by analyzing its runtime complexity.

Answer: D

Explanation:
The /optimize slash command in Visual Studio enhances the performance of the selected code by analyzing its runtime complexity and suggesting improvements.

NEW QUESTION # 64
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