Expert Answers to Amazon Web Services Exam AIF-C01 Questions

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AWS Certified AI Practitioner AWS Certified AI Practitioner Exam(AI1-C01)

AWS Certified AI Practitioner Exam(AI1-C01)

Last Update Dec 22, 2024
Total Questions : 87

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Questions 2

An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question.

Which solution meets these requirements with the LEAST implementation effort?

Options:

Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.

Add a role description to the prompt context that instructs the model of the age range that the response should target.

Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.

Summarize the response text depending on the age of the user so that younger users receive shorter responses.

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Questions 3

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?

Options:

Supervised learning

Unsupervised learning

Reinforcement learning

Reinforcement learning from human feedback (RLHF)

Discussion 0

Questions 4

A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.

Which solution will meet these requirements?

Options:

Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.

Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.

Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.

Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team's customer folders.

Discussion 0

Questions 5

Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team's VPC?

Options:

Amazon Personalize

Amazon SageMaker JumpStart