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Exam AWS Certified AI Practitioner AIF-C01 All Questions

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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 161 discussion

An airline company wants to build a conversational AI assistant to answer customer questions about flight schedules, booking, and payments. The company wants to use large language models (LLMs) and a knowledge base to create a text-based chatbot interface.

Which solution will meet these requirements with the LEAST development effort?

  • A. Train models on Amazon SageMaker Autopilot.
  • B. Develop a Retrieval Augmented Generation (RAG) agent by using Amazon Bedrock.
  • C. Create a Python application by using Amazon Q Developer.
  • D. Fine-tune models on Amazon SageMaker Jumpstart.
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Suggested Answer: B 🗳️

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65703c1
2 weeks, 6 days ago
Selected Answer: B
B is the correct answer
upvoted 1 times
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rinip86277
1 month, 2 weeks ago
Selected Answer: B
B provides the easiest, fastest path to a conversational AI with integrated knowledge retrieval.
upvoted 1 times
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neil1985_jy
1 month, 3 weeks ago
Selected Answer: B
1. Amazon Bedrock provides fully managed access to foundation models (like Anthropic Claude or Amazon Titan) without needing to train or fine-tune. 2 With RAG, you can connect these models to your knowledge base (e.g., flight schedules, booking policies) to generate accurate, context-aware responses. 3 Bedrock supports agents, which can orchestrate workflows, call APIs (like payment systems), and handle multi-turn conversations—perfect for a chatbot. 4 It’s serverless, scalable, and integrates easily with other AWS services like Lambda, S3, and OpenSearch.
upvoted 1 times
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026dda3
2 months, 2 weeks ago
Selected Answer: B
Amazon Bedrock is a fully managed service that offers a choice of high-performing Foundation Models (FMs) and provides capabilities to build generative AI applications with security and privacy. Amazon Bedrock Agents specifically helps you build generative AI applications that can run multi-step tasks across company systems and data sources, simplifying the process of building conversational AI applications.
upvoted 2 times
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Rcosmos
2 months, 2 weeks ago
Selected Answer: U
Amazon Bedrock permite usar LLMs prontos (como Anthropic Claude, AI21, Meta, etc.) sem necessidade de treinar ou ajustar modelos manualmente. A abordagem RAG (Retrieval-Augmented Generation) permite: Integrar os modelos de linguagem com bases de conhecimento externas, como FAQs, documentos, bases de dados de voos, etc. Fornecer respostas precisas e atualizadas com base nos dados da empresa. Reduzir drasticamente o esforço de desenvolvimento, pois não exige ajuste fino, nem infraestrutura para treinar modelos. Com Bedrock + RAG, é possível construir um chatbot poderoso, seguro e conectado aos dados corporativos com mínimo código.
upvoted 1 times
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