Free Amazon AIF-C01 Exam Questions

Question 1

A financial services company is exploring the use of generative AI to automate report generation and enhance customer insights. As part of this effort, the team is evaluating different AI models and technologies, including Foundation Models (FMs), to understand their capabilities and how they can be applied to improve efficiency. The team needs to clarify key characteristics and features of Foundation Models to determine if they align with the company's objectives.Which of the following statements is correct regarding Foundation Models (FMs) in the context of generative AI?

A : FMs use self-supervised learning to create labels from input data and fine-tuning an FM is a self-supervised learning process as well

B : FMs use supervised learning to create labels from input data and fine-tuning an FM is a supervised learning process as well

C : FMs use self-supervised learning to create labels from input data, however, fine-tuning an FM is a supervised learning process

D : FMs use supervised learning to create labels from input data, however, fine-tuning an FM is a self-supervised learning process

Answer: C

Question 2

A company is using Amazon Bedrock and it wants to set an upper limit on the number of tokens returned in the model's response.Which of the following inference parameters would you recommend for the given use case?

A : Response length

B : Stop sequence

C : Top P

D : Top K

Answer: A

Question 3

A company is using Amazon Bedrock and it wants to set an upper limit on the number of tokens returned in the model's response.Which of the following inference parameters would you recommend for the given use case?

A : Response length

B : Stop sequence

C : Top P

D : Top K

Answer: A

Question 4

Which statement best defines the use of MLflow with Amazon SageMaker ?

A : Label data using human-in-the-loop

B : Manage machine learning experiments

C : Perform automatic model tuning

D : Leverage no-code ML

Answer: B

Question 5

Which of the following services is specifically designed to provide insights into model predictions by explaining how input features contribute to the final output?

A : Amazon SageMaker Clarify

B : Amazon SageMaker Feature Store

C : Amazon SageMaker Model Monitor

D : Amazon SageMaker Canvas

Answer: A