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 06, 2026

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Question 1

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 2

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

Question 3

A company is deploying a generative AI model on Amazon Bedrock and needs to reduce the cost of usage while using prompt examples of up to 10 sample tasks as part of each input.Which approach would be the most effective in minimizing the costs associated with model usage?

A : The company should reduce the temperature inference parameter for the model

B : The company should reduce the number of tokens in the input

C : The company should reduce the top-P inference parameter for the model

D : The company should reduce the batch size while training the model

Answer: B

Question 4

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 5

A company wants to create a chatbot that answers questions about human resources policies. The company is using a large language model (LLM) and has a large digital documentation base. Which technique should the company use to optimize the generated responses?

A : Use Retrieval Augmented Generation (RAG).

B : Use few-shot prompting.

C : Set the temperature to 1.

D : Decrease the token size.

Answer: A

Page: 1 / 148

Total 737 Questions | Updated On: Mar 06, 2026

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