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: May 12, 2026

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Question 1

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 2

How can you prevent model-overfitting in machine learning?

A : By increasing the complexity of the model to ensure it captures all nuances in the training data

B : By only training the model on a small subset of the available data to reduce the amount of information it has to learn

C : By using techniques such as cross-validation, regularization, and pruning to simplify the model and improve its generalization

D : By avoiding any form of model validation or testing to prevent the model from learning incorrect patterns

Answer: C

Question 3

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 4

What is an example of structured data?

A : A file of text comments from an online forum

B : A compilation of video files that contains news broadcasts

C : A CSV file that consists of measurement data

D : Transcribed conversations between call center agents and customers

Answer: C

Question 5

Consider a scenario where a fully-managed AWS service needs to be used for automating the extraction of insights from legal briefs such as contracts and court records.What do you recommend?

A : Amazon Translate

B : Amazon Comprehend

C : Amazon Rekognition

D : Amazon Transcribe

Answer: B

Page: 1 / 148

Total 737 Questions | Updated On: May 12, 2026

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