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AWS Certified AI Practitioner AWS Certified AI Practitioner Exam

AWS Certified AI Practitioner Exam

Last Update Jan 9, 2026
Total Questions : 348

To help you prepare for the AIF-C01 Amazon Web Services exam, we are offering free AIF-C01 Amazon Web Services exam questions. All you need to do is sign up, provide your details, and prepare with the free AIF-C01 practice questions. Once you have done that, you will have access to the entire pool of AWS Certified AI Practitioner Exam AIF-C01 test questions which will help you better prepare for the exam. Additionally, you can also find a range of AWS Certified AI Practitioner Exam resources online to help you better understand the topics covered on the exam, such as AWS Certified AI Practitioner Exam AIF-C01 video tutorials, blogs, study guides, and more. Additionally, you can also practice with realistic Amazon Web Services AIF-C01 exam simulations and get feedback on your progress. Finally, you can also share your progress with friends and family and get encouragement and support from them.

Questions 2

A company needs to train an ML model to classify images of different types of animals. The company has a large dataset of labeled images and will not label more data. Which type of learning should the company use to train the model?

Options:

A.  

Supervised learning.

B.  

Unsupervised learning.

C.  

Reinforcement learning.

D.  

Active learning.

Discussion 0
Questions 3

A company has deployed an AI application in production on AWS. The application's responses have become less accurate over time. The company needs a solution to send alerts when the application performance drifts.

Which AWS service or feature will meet this requirement?

Options:

A.  

Amazon Augmented AI (Amazon A2I)

B.  

Amazon SageMaker Model Monitor

C.  

Amazon Rekognition

D.  

AWS Trusted Advisor

Discussion 0
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Questions 4

An AI practitioner is developing a prompt for large language models (LLMs) in Amazon Bedrock. The AI practitioner must ensure that the prompt works across all Amazon Bedrock LLMs.

Which characteristic can differ across the LLMs?

Options:

A.  

Maximum token count

B.  

On-demand inference parameter support

C.  

The ability to control model output randomness

D.  

Compatibility with Amazon Bedrock Guardrails

Discussion 0
Questions 5

Which statement describes a generative AI use case for multimodal models?

Options:

A.  

Deploy multiple scalable and cost-effective versions of a model.

B.  

Process large amounts of data to train multiple models.

C.  

Write code in multiple programming languages.

D.  

Process different data types, such as images, audio, and videos.

Discussion 0
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