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Exam GitHub-Copilot PDF - Download GitHub-Copilot Pdf

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Posted on: 05/12/25

Holding a certification in a certain field definitely shows that one have a good command of the GitHub-Copilot knowledge and professional skills in the related field. However, the majority of the candidates for the GitHub-Copilot exam are those who do not have enough spare time. But our company can provide the anecdote for you--our GitHub-Copilot Study Materials. Under the guidance of our GitHub-Copilot exam practice, you can definitely pass the exam as well as getting the related certification with the minimum time and efforts. Our GitHub-Copilot exam questions will never let you down.

GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 4
  • 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 5
  • How GitHub Copilot Works and Handles DataThis 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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GitHub CopilotCertification Exam Sample Questions (Q59-Q64):

NEW QUESTION # 59
What is a benefit of using custom models in GitHub Copilot?

  • A. Responses use the organization's LLM engine
  • B. Responses are faster to produce and appear sooner
  • C. Responses are guaranteed to be correct
  • D. Responses use practices and patterns in your repositories

Answer: D

Explanation:
Custom models in GitHub Copilot allow the tool to learn from the specific code patterns and practices within your repositories. This results in suggestions that are more aligned with your organization's coding standards and conventions, improving the relevance and accuracy of the generated code.


NEW QUESTION # 60
What content can be configured to be excluded with content exclusions? (Each correct answer presents part of the solution. Choose three.)

  • A. Gists
  • B. Files
  • C. Lines in files
  • D. Repositories
  • E. Folders

Answer: B,D,E

Explanation:
Content exclusions allow you to exclude files, folders, and repositories from being used by GitHub Copilot.


NEW QUESTION # 61
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 increase development lead time by providing irrelevant suggestions.
  • C. GitHub Copilot may decrease developer velocity by requiring too much time in prompt engineering.
  • 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 # 62
Why might a Generative AI (Gen AI) tool create inaccurate outputs?

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

Answer: C

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 # 63
Which of the following is correct about GitHub Copilot Knowledge Bases?

  • A. It is an Enterprise feature
  • B. All repos are indexed
  • C. All file types are indexed
  • D. Indexing is static

Answer: A

Explanation:
GitHub Copilot Knowledge Bases is an Enterprise feature that allows the tool to use an organization's internal documentation and code for more accurate and relevant suggestions.


NEW QUESTION # 64
......

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