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AWS Certified AI Practitioner Exam

Last Update 5 days ago Total Questions : 177

The AWS Certified AI Practitioner Exam content is now fully updated, with all current exam questions added 5 days ago. Deciding to include AIF-C01 practice exam questions in your study plan goes far beyond basic test preparation.

You'll find that our AIF-C01 exam questions frequently feature detailed scenarios and practical problem-solving exercises that directly mirror industry challenges. Engaging with these AIF-C01 sample sets allows you to effectively manage your time and pace yourself, giving you the ability to finish any AWS Certified AI Practitioner Exam practice test comfortably within the allotted time.

Question # 4

A company is building a mobile app for users who have a visual impairment. The app must be able to hear what users say and provide voice responses.

Which solution will meet these requirements?

A.

Use a deep learning neural network to perform speech recognition.

B.

Build ML models to search for patterns in numeric data.

C.

Use generative AI summarization to generate human-like text.

D.

Build custom models for image classification and recognition.

Question # 5

A financial company is using ML to help with some of the company's tasks.

Which option is a use of generative AI models?

A.

Summarizing customer complaints

B.

Classifying customers based on product usage

C.

Segmenting customers based on type of investments

D.

Forecasting revenue for certain products

Question # 6

A company wants to develop ML applications to improve business operations and efficiency.

Select the correct ML paradigm from the following list for each use case. Each ML paradigm should be selected one or more times. (Select FOUR.)

• Supervised learning

• Unsupervised learning

Question # 7

A company wants to build and deploy ML models on AWS without writing any code.

Which AWS service or feature meets these requirements?

A.

Amazon SageMaker Canvas

B.

Amazon Rekognition

C.

AWS DeepRacer

D.

Amazon Comprehend

Question # 8

A publishing company built a Retrieval Augmented Generation (RAG) based solution to give its users the ability to interact with published content. New content is published daily. The company wants to provide a near real-time experience to users.

Which steps in the RAG pipeline should the company implement by using offline batch processing to meet these requirements? (Select TWO.)

A.

Generation of content embeddings

B.

Generation of embeddings for user queries

C.

Creation of the search index

D.

Retrieval of relevant content

E.

Response generation for the user

Question # 9

A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings from a generative AI model as vectors in the database.

Which AWS service will meet these requirements?

A.

Amazon Athena

B.

Amazon Aurora PostgreSQL

C.

Amazon Redshift

D.

Amazon EMR

Question # 10

A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information.

Which action will reduce these risks?

A.

Create a prompt template that teaches the LLM to detect attack patterns.

B.

Increase the temperature parameter on invocation requests to the LLM.

C.

Avoid using LLMs that are not listed in Amazon SageMaker.

D.

Decrease the number of input tokens on invocations of the LLM.

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