AWS Certified AI Practitioner Exam
Last Update 3 days ago
Total Questions : 365
Dive into our fully updated and stable AIF-C01 practice test platform, featuring all the latest AWS Certified AI Practitioner exam questions added this week. Our preparation tool is more than just a Amazon Web Services study aid; it's a strategic advantage.
Our AWS Certified AI Practitioner practice questions crafted to reflect the domains and difficulty of the actual exam. The detailed rationales explain the 'why' behind each answer, reinforcing key concepts about AIF-C01. Use this test to pinpoint which areas you need to focus your study on.
A company is developing an ML model to support the company's retail application. The company wants to use information that the model has produced from previous tasks to increase the learning speed of the model.
Which model training solution will meet these requirements?
A company is building a generative AI application to help customers make travel reservations. The application will process customer requests and invoke the appropriate API calls to complete reservation transactions.
Which Amazon Bedrock resource will meet these requirements?
A company is building an AI application to automate business processes. The company uses a foundation model (FM) to support the application.
The company needs to select datasets to assess the quality of the AI model's behavior.
Which type of datasets will meet these requirements?
Which AI technique combines large language models (LLMs) with external knowledge bases to improve response accuracy?
A financial company has offices in different countries worldwide. The company requires that all API calls between generative AI applications and foundation models (FM) must not travel across the public internet.
Which AWS service should the company use?
A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.
Which Amazon SageMaker inference option will meet these requirements?
A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer.
What should the company do to meet these requirements?
A company wants to generate synthetic data responses for multiple prompts from a large volume of data. The company wants to use an API method to generate the responses. The company does not need to generate the responses immediately.
A company is using a large language model (LLM) on Amazon Bedrock to build a chatbot. The chatbot processes customer support requests. To resolve a request, the customer and the chatbot must interact a few times.
Which solution gives the LLM the ability to use content from previous customer messages?
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.
Which additional data does the company need to meet these requirements?
TESTED 19 Jan 2026
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