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AWS Certified AI Practitioner • STUDY MODE

Practice Quiz

QUESTION 1 OF 9

A business analyst needs to summarize multiple product documents and query their contents through an interactive dialogue. They have no prior coding experience and must implement this solution immediately using Amazon SageMaker Canvas. Which specific functionality within Amazon SageMaker Canvas meets these requirements?

A
Canvas chatCorrect Answer
B
Ready-to-use models
C
Custom numeric prediction models
D
Custom multi-category text prediction models
Explanation:

Canvas chat leverages open-source and Amazon LLMs to allow users to generate content, summarize or categorize documents, and answer questions without writing code. This directly supports the scenario requirements.

QUESTION 2 OF 9

Amazon SageMaker Canvas provides Ready-to-use models that allow users to quickly extract insights from data without building a custom model. Which underlying AWS services power these Ready-to-use models?

A
Amazon Rekognition, Amazon Textract, and Amazon ComprehendCorrect Answer
B
Amazon Bedrock, Amazon SageMaker JumpStart, and Amazon Lex
C
Amazon Kendra, Amazon Translate, and Amazon Transcribe
D
Amazon Personalize, Amazon Forecast, and Amazon Rekognition
Explanation:

According to the facts, Ready-to-use models in Amazon SageMaker Canvas are powered by Amazon AI services, specifically Amazon Rekognition, Amazon Textract, and Amazon Comprehend.

QUESTION 3 OF 9

When a business user wants to build and train their own machine learning models using Amazon SageMaker Canvas without coding, they can choose from specific supported custom model types. Which of the following lists the exact custom model types supported by Amazon SageMaker Canvas?

A
Numeric prediction, categorical prediction (binary and multi-class), time series forecasting, single-label image prediction, and multi-category text predictionCorrect Answer
B
Generative text creation, sentiment analysis, speech-to-text translation, and real-time video streaming analysis
C
Object detection, multi-label image classification, tabular clustering, and reinforcement learning
D
Anomaly detection, document layout parsing, semantic search, and dialogue generation
Explanation:

Amazon SageMaker Canvas supports specific custom model types including numeric prediction, categorical prediction (binary and multi-class), time series forecasting, single-label image prediction, and multi-category text prediction.

QUESTION 4 OF 9

A business analyst wants to analyze document text and image files to generate predictions. The analyst has no coding experience and wants to get predictions immediately without building or training any custom models. Which option in Amazon SageMaker Canvas best meets these requirements?

A
Ready-to-use models powered by Amazon AI servicesCorrect Answer
B
Custom model training for categorical predictions
C
Custom model training for time series forecasting
D
Canvas chat functionality utilizing LLMs
Explanation:

Amazon SageMaker Canvas features Ready-to-use models powered by Amazon AI services such as Amazon Rekognition, Amazon Textract, and Amazon Comprehend. This allows users to generate predictions without building or training a custom model, and without writing any code.

QUESTION 5 OF 9

A team wants to use Amazon SageMaker Canvas as a productivity tool to assist with content generation, summarizing lengthy documents, and categorizing text. Which feature of SageMaker Canvas should they use to perform these tasks?

A
Canvas chat functionalityCorrect Answer
B
Ready-to-use models
C
Custom classification models
D
Custom regression models
Explanation:

Canvas chat is a productivity feature in Amazon SageMaker Canvas that utilizes open-source and Amazon LLMs to assist users with content generation, document summarization, document categorization, and question answering.

QUESTION 6 OF 9

When building a custom machine learning model without writing code in Amazon SageMaker Canvas, which types of custom model training are supported?

A
Regression, binary/multi-class classification, time series forecasting, image classification, and multi-class text classificationCorrect Answer
B
Reinforcement learning, unsupervised clustering, and generative adversarial networks (GANs)
C
Video summarization, speech-to-text translation, and anomaly detection
D
Dynamic pricing optimization, natural language translation, and semantic search
Explanation:

Amazon SageMaker Canvas supports custom model training for several specific types of machine learning tasks without code: regression (numeric prediction), binary and multi-class classification (categorical prediction), time series forecasting, image classification (single-label image prediction), and multi-class text classification (multi-category text prediction).

QUESTION 7 OF 9

A business analyst needs to extract text from documents and identify objects in images. They have no prior coding experience and want to generate predictions without writing code. Additionally, they want to use pre-existing capabilities directly and avoid building or training any custom models. Which SageMaker Canvas feature meets these requirements?

A
Canvas Chat
B
Canvas Custom Models
C
Canvas Ready-to-use modelsCorrect Answer
D
Canvas Notebook instances
Explanation:

Amazon SageMaker Canvas allows users to generate predictions without writing code. For users who do not want to build custom models, SageMaker Canvas offers Ready-to-use models which are powered by existing Amazon AI services like Amazon Rekognition, Amazon Textract, and Amazon Comprehend. Canvas Chat and Custom Models do not fit this specific need, and Notebook instances require writing code.

QUESTION 8 OF 9

Amazon SageMaker Canvas supports several types of custom models to solve diverse business problems without writing code. Which of the following is an officially supported custom model type in SageMaker Canvas?

A
Multi-category text predictionCorrect Answer
B
Unsupervised clustering models
C
Reinforcement learning policy models
D
Graph neural network predictions
Explanation:

Amazon SageMaker Canvas supports specific custom model types for no-code predictions, including numeric prediction, categorical prediction, time series forecasting, single-label image prediction, and multi-category text prediction. Other options like clustering, reinforcement learning, or graph neural networks are not supported.

QUESTION 9 OF 9

A business user wants to increase productivity by generating marketing content, summarizing long reports, categorizing internal documents, and interactive question answering. They want to use open-source and Amazon Large Language Models (LLMs) via an interactive interface. Which SageMaker Canvas feature is designed for this workload?

A
Canvas Custom numeric prediction models
B
Canvas ChatCorrect Answer
C
Canvas Ready-to-use models
D
Canvas Time series forecasting
Explanation:

Canvas Chat is a feature that leverages open-source and Amazon LLMs to assist users with content generation, document summarization, document categorization, and question answering. Other Canvas options like custom numeric prediction, ready-to-use models, or time series forecasting do not provide this interactive LLM-based chat functionality.

Ready to test your recall?

A business analyst needs to summarize multiple product documents and query their contents through an interactive dialogue. They have no prior coding experience and must implement this solution immediately using Amazon SageMaker Canvas. Which specific functionality within Amazon SageMaker Canvas meets these requirements?

A
Canvas chat
B
Ready-to-use models
C
Custom numeric prediction models
D
Custom multi-category text prediction models

How confident are you in this answer?