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Perfect New GitHub-Copilot Exam Pdf - Win Your GitHub Certificate with Top Score

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GitHub GitHub-Copilot Exam Syllabus Topics:

Topic
Details

Topic 1

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.

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

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 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.

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GitHub CopilotCertification Exam Sample Questions (Q57-Q62):

NEW QUESTION # 57
GitHub Copilot in the Command Line Interface (CLI) can be used to configure the following settings: (Each correct answer presents part of the solution. Choose two.)

A. The default execution confirmation
B. Usage analytics
C. The default editor
D. GitHub CLI subcommands

Answer: A,B

Explanation:
GitHub Copilot in the CLI allows configuration of settings such as the default execution confirmation and usage analytics. These settings help tailor the CLI experience to the user's preferences.

NEW QUESTION # 58
Why might a Generative AI (Gen AI) tool create inaccurate outputs?

A. The training data might contain biases or inconsistencies.
B. The Gen AI tool is experiencing downtime and is not fully recovered.
C. The Gen AI tool is programmed with a focus on creativity over factual accuracy.
D. The Gen AI tool is overloaded with too many requests at once.

Answer: A

Explanation:
Gen AI tools can produce inaccurate outputs if the training data contains biases or inconsistencies, which can lead to flawed or misleading results.

NEW QUESTION # 59
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)

A. Provide specific success criteria
B. Provide all information about the utilized files
C. Provide insight on where to get the content from to get a response
D. Provide links to supporting documentation

Answer: A,D

Explanation:
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.

NEW QUESTION # 60
What is the process behind identifying public code matches when using a public code filter enabled in GitHub Copilot?

A. Running code suggestions through filters designed to detect public code
B. Comparing suggestions against public code using machine learning.
C. Analyzing the context and structure of the code being written
D. Reviewing the user's browsing history to identify public repositories

Answer: A

Explanation:
When the public code filter is enabled, GitHub Copilot runs code suggestions through filters designed to detect matches with publicly available code. This helps prevent the generation of code that might infringe on copyright or licensing agreements.

NEW QUESTION # 61
How long does it take content exclusion to add or be updated?

A. 45 - 60 minutes
B. 60 - 90 minutes
C. Up to 30 minutes
D. 24 hours

Answer: C

Explanation:
Content exclusions typically take up to 30 minutes to be added or updated.

NEW QUESTION # 62
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