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AIF-C01 Practice Questions

AWS Certified AI Practitioner Exam

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Total Questions : 401

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 free 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.

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Question # 11

An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.

How should the AI practitioner prevent responses based on confidential data?

Options:

A.  

Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.

B.  

Mask the confidential data in the inference responses by using dynamic data masking.

C.  

Encrypt the confidential data in the inference responses by using Amazon SageMaker.

D.  

Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).

Discussion 0
Question # 12

A company wants to identify harmful language in the comments section of social media posts by using an ML model. The company will not use labeled data to train the model. Which strategy should the company use to identify harmful language?

Options:

A.  

Use Amazon Rekognition moderation.

B.  

Use Amazon Comprehend toxicity detection.

C.  

Use Amazon SageMaker AI built-in algorithms to train the model.

D.  

Use Amazon Polly to monitor comments.

Discussion 0
Question # 13

A financial company is developing a fraud detection system that flags potential fraud cases in credit card transactions. Employees will evaluate the flagged fraud cases. The company wants to minimize the amount of time the employees spend reviewing flagged fraud cases that are not actually fraudulent.

Which evaluation metric meets these requirements?

Options:

A.  

Recall

B.  

Accuracy

C.  

Precision

D.  

Lift chart

Discussion 0
Question # 14

A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images.

Which solution will meet these requirements?

Options:

A.  

Implement moderation APIs.

B.  

Retrain the model with a general public dataset.

C.  

Perform model validation.

D.  

Automate user feedback integration.

Discussion 0
Question # 15

A company wants to upload customer service email messages to Amazon S3 to develop a business analysis application. The messages sometimes contain sensitive data. The company wants to receive an alert every time sensitive information is found.

Which solution fully automates the sensitive information detection process with the LEAST development effort?

Options:

A.  

Configure Amazon Macie to detect sensitive information in the documents that are uploaded to Amazon S3.

B.  

Use Amazon SageMaker endpoints to deploy a large language model (LLM) to redact sensitive data.

C.  

Develop multiple regex patterns to detect sensitive data. Expose the regex patterns on an Amazon SageMaker notebook.

D.  

Ask the customers to avoid sharing sensitive information in their email messages.

Discussion 0
Question # 16

An ecommerce company is deploying a chatbot. The chatbot will give users the ability to ask questions about the company ' s products and receive details on users ' orders. The company must implement safeguards for the chatbot to filter harmful content from the input prompts and chatbot responses.

Which AWS feature or resource meets these requirements?

Options:

A.  

Amazon Bedrock Guardrails

B.  

Amazon Bedrock Agents

C.  

Amazon Bedrock inference APIs

D.  

Amazon Bedrock custom models

Discussion 0
Question # 17

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?

Options:

A.  

AWS PrivateLink

B.  

Amazon

C.  

Amazon CloudFront

D.  

AWS CloudTrail

Discussion 0
Question # 18

Which AWS service or feature stores embeddings In a vector database for use with foundation models (FMs) and Retrieval Augmented Generation (RAG)?

Options:

A.  

Amazon SageMaker Ground Truth

B.  

Amazon OpenSearch Service

C.  

Amazon Transcribe

D.  

Amazon Textract

Discussion 0
Question # 19

Which AI technique combines large language models (LLMs) with external knowledge bases to improve response accuracy?

Options:

A.  

Reinforcement learning (RL)

B.  

Natural language processing (NLP)

C.  

Retrieval Augmented Generation (RAG)

D.  

Transfer learning

Discussion 0
Question # 20

Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

Options:

A.  

Integration with Amazon S3 for object storage

B.  

Support for geospatial indexing and queries

C.  

Scalable index management and nearest neighbor search capability

D.  

Ability to perform real-time analysis on streaming data

Discussion 0
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