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Amazon AWS Certified AI Practitioner Sample Questions:

1. A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products.
Which methodology should the company use to meet these requirements?

A) Supervised learning
B) Reinforcement learning from human feedback (RLHF)
C) Reinforcement learning
D) Unsupervised learning

2. A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to know how much information can fit into one prompt.
Which consideration will inform the company's decision?

A) Context window
B) Temperature
C) Model size
D) Batch size

3. A company wants to build an interactive application for children that generates new stories based on classic stories. The company wants to use Amazon Bedrock and needs to ensure that the results and topics are appropriate for children.
Which AWS service or feature will meet these requirements?

A) Guardrails for Amazon Bedrock
B) Agents for Amazon Bedrock
C) Amazon Bedrock playgrounds
D) Amazon Rekognition

4. An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images.
Which type of FM should the AI practitioner use to power the search application?

A) Multi-modal generation model
B) Text embedding model
C) Multi-modal embedding model
D) Image generation model

5. A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks.
Which solution will meet this requirement?

A) Use Amazon Inspector to monitor SageMaker Studio.
B) Configure SageMaker to use a VPC with an S3 endpoint.
C) Configure SageMaker to use S3 Glacier Deep Archive.
D) Use Amazon Macie to monitor SageMaker Studio.

Solutions: