AIF-C01 Deutsch & AIF-C01 Prüfungsübungen

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AIF-C01 Prüfungsübungen, AIF-C01 Quizfragen Und Antworten

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Amazon AIF-C01 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Applications of Foundation Models: This domain examines how foundation models, like large language models, are used in practical applications. It is designed for those who need to understand the real-world implementation of these models, including solution architects and data engineers who work with AI technologies to solve complex problems.
Thema 2	Guidelines for Responsible AI: This domain highlights the ethical considerations and best practices for deploying AI solutions responsibly, including ensuring fairness and transparency. It is aimed at AI practitioners, including data scientists and compliance officers, who are involved in the development and deployment of AI systems and need to adhere to ethical standards.
Thema 3	Fundamentals of Generative AI: This domain explores the basics of generative AI, focusing on techniques for creating new content from learned patterns, including text and image generation. It targets professionals interested in understanding generative models, such as developers and researchers in AI.
Thema 4	Security, Compliance, and Governance for AI Solutions: This domain covers the security measures, compliance requirements, and governance practices essential for managing AI solutions. It targets security professionals, compliance officers, and IT managers responsible for safeguarding AI systems, ensuring regulatory compliance, and implementing effective governance frameworks.
Thema 5	Fundamentals of AI and ML: This domain covers the fundamental concepts of artificial intelligence (AI) and machine learning (ML), including core algorithms and principles. It is aimed at individuals new to AI and ML, such as entry-level data scientists and IT professionals.

Amazon AWS Certified AI Practitioner AIF-C01 Prüfungsfragen mit Lösungen (Q40-Q45):

40. Frage
A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.
Which solution will meet this requirement?

A. Enable model invocation logging
B. Create an Amazon Bedrock knowledge base
C. Use a different FM
D. Choose a lower temperature value

Antwort: B

41. Frage
A company wants to build an interactive application for children that generates new stories based on classic stories. The company wants to use Amazon Bedrock and needs to ensure that the results and topics are appropriate for children.
Which AWS service or feature will meet these requirements?

A. Amazon Bedrock playgrounds
B. Amazon Rekognition
C. Guardrails for Amazon Bedrock
D. Agents for Amazon Bedrock

Antwort: C

Begründung:
Amazon Bedrock is a service that provides foundational models for building generative AI applications.
When creating an application for children, it is crucial to ensure that the generated content is appropriate for the target audience. "Guardrails" in Amazon Bedrock provide mechanisms to control the outputs and topics of generated content to align with desired safety standards and appropriateness levels.
* Option C (Correct): "Guardrails for Amazon Bedrock": This is the correct answer because guardrails are specifically designed to help users enforce content moderation, filtering, and safety checks on the outputs generated by models in Amazon Bedrock. For a children's application, guardrails ensure that all content generated is suitable and appropriate for the intended audience.
* Option A: "Amazon Rekognition" is incorrect. Amazon Rekognition is an image and video analysis service that can detect inappropriate content in images or videos, but it does not handle text or story generation.
* Option B: "Amazon Bedrock playgrounds" is incorrect because playgrounds are environments for experimenting and testing model outputs, but they do not inherently provide safeguards to ensure content appropriateness for specific audiences, such as children.
* Option D: "Agents for Amazon Bedrock" is incorrect. Agents in Amazon Bedrock facilitate building AI applications with more interactive capabilities, but they do not provide specific guardrails for ensuring content appropriateness for children.
AWS AI Practitioner References:
* Guardrails in Amazon Bedrock: Designed to help implement controls that ensure generated content is safe and suitable for specific use cases or audiences, such as children, by moderating and filtering inappropriate or undesired content.
* Building Safe AI Applications: AWS provides guidance on implementing ethical AI practices, including using guardrails to protect against generating inappropriate or biased content.

42. Frage
A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteri a. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers.
Which actions should the company take to meet these requirements? (Select TWO.)

A. Ensure that the model's inference time is within the accepted limits.
B. Use the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate.
C. Detect imbalances or disparities in the data.
D. Ensure that the model runs frequently.
E. Evaluate the model's behavior so that the company can provide transparency to stakeholders.

Antwort: C,E

43. Frage
A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.
Which ML algorithm meets these requirements?

A. Decision trees
B. Logistic regression
C. Linear regression
D. Neural networks

Antwort: A

44. Frage
A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.
Which solution will meet these requirements?

A. Encrypt and secure training data by using Amazon Macie.
B. Gather more data. Use Amazon Rekognition to add custom labels to the data.
C. Configure the security and compliance by using Amazon Inspector.
D. Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.

Antwort: D

45. Frage
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