AIF-C01퍼펙트최신덤프자료최신시험기출문제

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Amazon AIF-C01 Exam Overview:

Certification Vendor:	Amazon Web Services (AWS)
Exam Name:	AWS Certified AI Practitioner (AIF-C01)
Exam Number:	AIF-C01
Available Languages:	Spanish, Korean, Japanese, Simplified Chinese, Portuguese (Brazil), English
Exam Format:	Multiple response, Multiple choice
Exam Price:	$100 USD
Passing Score:	700/1000
Certificate Validity Period:	3 years
Real Exam Qty:	65
Exam Duration:	90 minutes
Related Certifications:	AWS Certified Cloud Practitioner
Recommended Training:	AWS Certified AI Practitioner Official Exam Guide AWS Skill Builder - AI Practitioner Learning Plan
Exam Registration:	AWS Certification Portal AWS Training and Certification Registration
Sample Questions:	Amazon AIF-C01 Sample Questions
Exam Way:	Online proctored exam or in-person test center
Pre Condition:	No formal prerequisites required. Recommended: basic understanding of cloud computing and general AI/ML concepts.
Official Syllabus URL:	https://aws.amazon.com/certification/certified-ai-practitioner/

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AIF-C01최신 업데이트버전 덤프 & AIF-C01퍼펙트 최신버전 문제

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Amazon AIF-C01 시험요강:

주제	소개
주제 1	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.
주제 2	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.
주제 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.
주제 4	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.
주제 5	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.

최신 AWS Certified AI AIF-C01 무료샘플문제 (Q279-Q284):

질문 # 279
A retail company wants to build an ML model to recommend products to customers. The company wants to build the model based on responsible practices. Which practice should the company apply when collecting data to decrease model bias?

A. Collect data from customers who have a past purchase history.
B. Ensure that the data is from a publicly available dataset.
C. Ensure that the data is balanced and collected from a diverse group.
D. Use data from only customers who match the demography of the company's overall customer base.

정답：C

설명：
The retail company wants to build an ML model for product recommendations using responsible practices to decrease model bias. Collecting balanced and diverse data ensures the model does not favor specific groups, reducing bias and promoting fairness, a key responsible AI practice.
Exact Extract from AWS AI Documents:
From the AWS AI Practitioner Learning Path:
"To reduce model bias, it is critical to collect balanced and diverse data that represents various demographics and user groups. This practice ensures fairness and prevents the model from disproportionately favoring certain populations." (Source: AWS AI Practitioner Learning Path, Module on Responsible AI) Detailed Explanation:
* Option A: Use data from only customers who match the demography of the company's overall customer base.Limiting data to a specific demographic may reinforce existing biases, failing to address underrepresented groups and increasing bias.
* Option B: Collect data from customers who have a past purchase history.Focusing only on customers with purchase history may exclude new users, potentially introducing bias, and does not address diversity.
* Option C: Ensure that the data is balanced and collected from a diverse group.This is the correct answer. A balanced and diverse dataset reduces bias by ensuring the model learns from a representative sample, aligning with responsible AI practices.
* Option D: Ensure that the data is from a publicly available dataset.Public datasets may not be diverse or representative of the company's customer base and could introduce unrelated biases, failing to address fairness.
References:
AWS AI Practitioner Learning Path: Module on Responsible AI
Amazon SageMaker Developer Guide: Bias and Fairness in ML (https://docs.aws.amazon.com/sagemaker
/latest/dg/clarify-bias.html)
AWS Documentation: Responsible AI Practices (https://aws.amazon.com/machine-learning/responsible-ai/)

질문 # 280
An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email notifications when an ISV's compliance reports become available.
Which AWS service can the company use to meet this requirement?

A. AWS Trusted Advisor
B. AWS Audit Manager
C. AWS Data Exchange
D. AWS Artifact

정답：D

설명：
The verified answer is B. AWS Artifact. AWS Artifact provides on-demand downloads of AWS security and compliance documents, including compliance reports and certifications. AWS documentation also states that AWS Artifact can provide security and compliance documents for independent software vendors who sell products on AWS Marketplace. This directly matches the requirement involving ISV compliance reports.
AWS Artifact documentation further explains that users can access AWS reports on the AWS reports tab and access independent software vendor reports on the Third-party reports tab. This confirms that AWS Artifact is the correct service for obtaining ISV compliance documentation.
The notification requirement also points to AWS Artifact. AWS documentation states that the AWS Artifact console can be used to configure email notifications for updates on agreements and reports in AWS Artifact. AWS Artifact sends those notifications through AWS User Notifications, and users can specify notification recipients and which notifications they receive.
AWS Audit Manager is incorrect because it helps automate evidence collection and compliance assessments for the customer's AWS usage. It does not primarily provide ISV compliance report notifications. AWS Trusted Advisor is incorrect because it provides best-practice recommendations for AWS accounts, not ISV report availability. AWS Data Exchange is incorrect because it is used to find, subscribe to, and use third-party data products. It is not the compliance report and notification portal.
Therefore, the correct service is AWS Artifact.

질문 # 281
A company stores millions of PDF documents in an Amazon S3 bucket. The company needs to extract the text from the PDFs, generate summaries of the text, and index the summaries for fast searching.
Which combination of AWS services will meet these requirements? (Select TWO.)

A. Amazon Translate
B. Amazon Textract
C. Amazon Transcribe
D. Amazon Bedrock
E. Amazon Polly

정답：B,D

설명：
Amazon Textract (E) automatically extracts text and structured data from scanned documents, such as PDFs.
Amazon Bedrock (B) offers access to LLMs (such as Amazon Titan or Anthropic Claude) for tasks like summarization and generating embeddings for search.
Workflow:
Amazon Textract extracts text from PDFs in S3.
Amazon Bedrock LLMs summarize the extracted text.
(Optional: Summaries can be indexed using Amazon OpenSearch or another search solution.) A (Translate) is for language translation, not extraction or summarization.
C (Transcribe) is for audio to text, not PDFs.
D (Polly) is for text-to-speech.
"Amazon Textract extracts text, forms, and tables from scanned documents... Bedrock provides generative AI models to perform summarization and other text generation tasks." (Reference: Amazon Textract, Amazon Bedrock, AWS GenAI RAG Reference)
"Amazon Textract extracts text, forms, and tables from scanned documents... Bedrock provides generative AI models to perform summarization and other text generation tasks." (Reference: Amazon Textract, Amazon Bedrock, AWS GenAI RAG Reference)

질문 # 282
A company is building a new generative AI chatbot. The chatbot uses an Amazon Bedrock foundation model (FM) to generate responses. During testing, the company notices that the chatbot is prone to prompt injection attacks.
What can the company do to secure the chatbot with the LEAST implementation effort?

A. Fine-tune the FM to avoid harmful responses.
B. Use Amazon Bedrock Guardrails content filters and denied topics.
C. Change the FM to a more secure FM.
D. Use chain-of-thought prompting to produce secure responses.

정답：B

설명：
Amazon Bedrock Guardrails allow developers to create safeguards that filter harmful content and prevent sensitive topics from being discussed. This functionality helps mitigate prompt injection attacks with minimal implementation effort. According to the official Amazon Bedrock documentation:
"You can configure Guardrails for Amazon Bedrock to define denied topics, use content filters, and apply sensitive information filters, offering protection against prompt injection attacks with minimal development effort."

질문 # 283
A company wants to implement a large language model (LLM)-based chatbot to provide customer service agents with real-time contextual responses to customers' inquiries. The company will use the company's policies as the knowledge base.

A. Use pre-training and data augmentation on the company policy data.
B. Implement Retrieval Augmented Generation (RAG) for in-context responses.
C. Fine-tune the LLM on the company policy data.
D. Retrain the LLM on the company policy data.

정답：B

설명：
Comprehensive and Detailed
Retraining or pre-training is costly and unnecessary for just using company policies.
Fine-tuning adapts models but is inefficient for frequently changing company documents.
Retrieval-Augmented Generation (RAG) is the best approach - it retrieves relevant policy documents from a knowledge base and feeds them into the model context in real time, ensuring accurate and up-to-date responses.
Reference:
AWS Documentation - RAG with Amazon Bedrock

질문 # 284
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