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AIF-C01 Practice Questions

AWS Certified AI Practitioner Exam

Last Update 11 hours ago
Total Questions : 365

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Question # 61

A company manually reviews all submitted resumes in PDF format. As the company grows, the company expects the volume of resumes to exceed the company's review capacity. The company needs an automated system to convert the PDF resumes into plain text format for additional processing.

Which AWS service meets this requirement?

Options:

A.  

Amazon Textract

B.  

Amazon Personalize

C.  

Amazon Lex

D.  

Amazon Transcribe

Discussion 0
Question # 62

A company is using large language models (LLMs) to develop online tutoring applications. The company needs to apply configurable safeguards to the LLMs. These safeguards must ensure that the LLMs follow standard safety rules when creating applications.

Which solution will meet these requirements with the LEAST effort?

Options:

A.  

Amazon Bedrock playgrounds

B.  

Amazon SageMaker Clarify

C.  

Amazon Bedrock Guardrails

D.  

Amazon SageMaker JumpStart

Discussion 0
Question # 63

A company wants to improve the accuracy of the responses from a generative AI application. The application uses a foundation model (FM) on Amazon Bedrock.

Which solution meets these requirements MOST cost-effectively?

Options:

A.  

Fine-tune the FM.

B.  

Retrain the FM.

C.  

Train a new FM.

D.  

Use prompt engineering.

Discussion 0
Question # 64

A company wants to build an interactive application for children that generates new stories based on classic stories. The company wants to use Amazon Bedrock and needs to ensure that the results and topics are appropriate for children.

Which AWS service or feature will meet these requirements?

Options:

A.  

Amazon Rekognition

B.  

Amazon Bedrock playgrounds

C.  

Guardrails for Amazon Bedrock

D.  

Agents for Amazon Bedrock

Discussion 0
Question # 65

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 # 66

Which option is an example of unsupervised learning?

Options:

A.  

Clustering data points into groups based on their similarity

B.  

Training a model to recognize images of animals

C.  

Predicting the price of a house based on the house's features

D.  

Generating human-like text based on a given prompt

Discussion 0
Question # 67

A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.

Which stage of the ML pipeline is the company currently in?

Options:

A.  

Data pre-processing

B.  

Feature engineering

C.  

Exploratory data analysis

D.  

Hyperparameter tuning

Discussion 0
Question # 68

A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur.

Which solution meets these requirements?

Options:

A.  

Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.

B.  

Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.

C.  

Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.

D.  

Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.

Discussion 0
Question # 69

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 # 70

A company wants to build a lead prioritization application for its employees to contact potential customers. The application must give employees the ability to view and adjust the weights assigned to different variables in the model based on domain knowledge and expertise.

Which ML model type meets these requirements?

Options:

A.  

Logistic regression model

B.  

Deep learning model built on principal components

C.  

K-nearest neighbors (k-NN) model

D.  

Neural network

Discussion 0
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