Free Amazon AIF-C01 Exam Questions

Become Amazon Certified with updated AIF-C01 exam questions and correct answers

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Total 737 Questions | Updated On: Mar 24, 2026

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Question 1

A machine learning team at a tech company is developing a generative AI model to automate text generation for customer support. As part of optimizing the model’s performance, the team needs to adjust both model parameters and hyperparameters but wants to clearly understand the distinctions between the two. Understanding these differences is crucial for fine-tuning the model and improving its output.Which of the following highlights the key differences between model parameters and hyperparameters in the context of generative AI?

A : Hyperparameters are values that define a model and its behavior in interpreting input and generating responses. Model parameters are values that can be adjusted for model customization to control the training process

B : Both Hyperparameters and model parameters are values that define a model and its behavior in interpreting input and generating responses

C : Model parameters are values that define a model and its behavior in interpreting input and generating responses. Hyperparameters are values that can be adjusted for model customization to control the training process

D : Both Hyperparameters and model parameters are values that can be adjusted for model customization to control the training process

Answer: C

Question 2

A bank has fine-tuned a large language model (LLM) to expedite the loan approval process. During an external audit of the model, the company discovered that the model was approving loans at a faster pace for a specific demographic than for other demographics. How should the bank fix this issue MOST cost-effectively?

A : Include more diverse training data. Fine-tune the model again by using the new data.

B : Use Retrieval Augmented Generation (RAG) with the fine-tuned model.

C : Use AWS Trusted Advisor checks to eliminate bias.

D : Pre-train a new LLM with more diverse training data.

Answer: A

Question 3

A financial company is developing a generative AI application for loan approval decisions. Thecompany needs the application output to be responsible and fair.

A : Review the training data to check for biases. Include data from all demographics in the training data.

B : Use a deep learning model with many hidden layers.

C : Keep the model's decision-making process a secret to protect proprietary algorithms.

D : Continuously monitor the model's performance on a static test dataset.

Answer: A

Question 4

A financial company is developing a generative AI application for loan approval decisions. Thecompany needs the application output to be responsible and fair.

A : Review the training data to check for biases. Include data from all demographics in the training data.

B : Use a deep learning model with many hidden layers.

C : Keep the model's decision-making process a secret to protect proprietary algorithms.

D : Continuously monitor the model's performance on a static test dataset.

Answer: A

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

Page: 1 / 148

Total 737 Questions | Updated On: Mar 24, 2026

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