Questão 27 — Amazon AIF-C01 Simulado | AWS Certified AI Practitioner Questões e Respostas

Explanation: The correct answer is A because Amazon SageMaker Canvas is designed specifically for users with little or no machine learning or programming experience. It provides a visual interface to build ML models by simply uploading data, performing analysis, and generating predictions using a no-code environment. From the AWS documentation: "Amazon SageMaker Canvas enables business analysts and other users to generate accurate ML predictions using a visual, point-and-click interface without writing code or having prior ML experience." This feature allows the user to: Import datasets (e.g., HR data) Automatically explore the data Select the prediction column (e.g., attrition) Train the model Generate and export predictions Explanation of other options: B . SageMaker Clarify is used to detect bias and explain ML predictions but not to build models or make predictions without code. C . SageMaker Model Monitor monitors model quality in production but doesn't build or train models. D . SageMaker Data Wrangler is used for data preprocessing and transformation but still requires some technical configuration. Referenced AWS AI/ML Documents and Study Guides: Amazon SageMaker Canvas Developer Guide AWS Certified Machine Learning Specialty Study Guide AutoML and No-Code Tools Section AWS Machine Learning Blog: "Predict Employee Attrition with SageMaker Canvas"