Free Amazon AIF-C01 Exam Questions

Match the following Amazon SageMaker services to the respective use cases:

A) SageMaker Data Wrangler

B) SageMaker Canvas

C) SageMaker Ground Truth

1) Harnessing human input across the ML lifecycle to improve the accuracy and relevancy of models

2) Offers 300+ pre-configured data transformations to prepare data for ML

3) No-code service with an intuitive, point-and-click interface

A tech company is developing an AI-powered customer support solution using Retrieval-Augmented Generation (RAG) with Amazon Bedrock to provide more accurate and context-aware responses. To achieve this, the company needs a database that can handle fast index lookups and similarity searches to quickly retrieve the most relevant documents or information from a large dataset. The ideal database solution should efficiently support search queries and rank results based on their relevance to the input provided by the user.Given these requirements, which database solution would be most appropriate for the company to use?

A security company is evaluating Amazon Rekognition to enhance its Machine Learning (ML) capabilities. However, the data science team needs to identify scenarios where Amazon Rekognition may not be the most suitable solution. Understanding these limitations will help the team select the right tools for different aspects of their security system.Given this context, which of the following use cases is NOT the right fit for Amazon Rekognition?

Which AWS service is specifically designed for converting medical speech to text, ensuring compliance with healthcare regulations such as HIPAA?

A company is deploying a generative AI model on Amazon Bedrock and needs to reduce the cost of usage while using prompt examples of up to 10 sample tasks as part of each input.Which approach would be the most effective in minimizing the costs associated with model usage?