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 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

Question 2

How would you differentiate between K-Means and K-Nearest Neighbors (KNN) algorithms in machine learning?

A : K-Means is primarily used for regression tasks, while KNN is used for reducing the dimensionality of data

B : K-Means is an unsupervised learning algorithm used for clustering data points into groups, while KNN is a supervised learning algorithm used for classifying data points based on their proximity to labeled examples

C : K-Means is a supervised learning algorithm used for classification, while KNN is an unsupervised learning algorithm used for clustering

D : K-Means requires labeled data to form clusters, whereas KNN does not use labeled data for making predictions

Answer: B

Question 3

Which deployment model is the right fit for workloads that can tolerate cold starts in Amazon SageMaker?

A : Batch transform

B : Real-time hosting services

C : Serverless Inference

D : Asynchronous Inference

Answer: C

Question 4

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 Transcribe

C : Amazon Comprehend

D : Amazon Rekognition

Answer: C

Question 5

Which of the following aptly summarizes the capabilities of Foundation Models?

A : Foundation models are limited to simple data processing tasks and cannot handle complex operations

B : Foundation models are designed to work exclusively with structured data and cannot process unstructured data like text or images

C : Foundation models can only perform a single task they were specifically trained for

D : Foundation models can perform a wide range of tasks across different domains by leveraging their extensive pre-training on large datasets

Answer: D

Page: 1 / 119

Total 595 Questions | Updated On: Feb 10, 2026

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