Free Amazon AIF-C01 Exam Questions

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

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Total 595 Questions | Updated On: Feb 10, 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

A company has implemented a chatbot powered by Amazon Bedrock to handle customer inquiries and support requests. While the chatbot is effective at providing automated responses, the company has noticed that some of the replies do not consistently match its desired tone — professional, empathetic, and friendly. To maintain brand consistency and ensure a positive customer experience, the company needs to align the chatbot’s responses with its specific communication style and standards.Which approach would be most effective for ensuring that the chatbot's responses are consistently aligned with the company's tone and style?

A : The company should iteratively test and adjust the chatbot prompts to ensure that its outputs consistently reflect the company's tone and style

B : The company should set a low limit on the number of tokens, which restricts the length of the chatbot's responses, thereby making the chatbot’s responses consistent

C : The company should use batch inferencing, a method that processes multiple input requests in one go to make the chatbot’s responses consistent

D : The company should adjust the temperature to reduce the randomness and creativity of the chatbot’s responses

Answer: A

Question 3

A company is building an ML model. The company collected new data and analyzed the data by creating a

correlation matrix, calculating statistics, and visualizing the data.

Which stage of the ML pipeline is the company currently in?

A : Data pre-processing

B : Feature engineering

C : Exploratory data analysis

D : Hyperparameter tuning

Answer: C

Question 4

A retail company is looking to streamline its machine learning workflows and improve collaboration between data science teams. The team is considering using MLflow with Amazon SageMaker to manage the end-to-end machine learning lifecycle. Understanding how MLflow integrates with Amazon SageMaker will help the team decide if this combination is the right fit for their machine learning project management needs.Given this context, which statement best defines the use of MLflow with Amazon SageMaker?

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

B : Leverage no-code ML

C : Manage machine learning experiments

D : Perform automatic model tuning

Answer: C

Question 5

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

Page: 1 / 119

Total 595 Questions | Updated On: Feb 10, 2026

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