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AIF-C01 AWS Certified AI Practitioner Exam(AI1-C01) Questions and Answers

Questions 4

A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.

Which solution will meet these requirements?

Options:

A.

Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.

B.

Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.

C.

Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.

D.

Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team's customer folders.

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Questions 5

A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive or negative.

Which prompt engineering strategy meets these requirements?

Options:

A.

Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.

B.

Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.

C.

Provide the new text passage to be classified without any additional context or examples.

D.

Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.

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Questions 6

A company is using a pre-trained large language model (LLM) to build a chatbot for product recommendations. The company needs the LLM outputs to be short and written in a specific language.

Which solution will align the LLM response quality with the company's expectations?

Options:

A.

Adjust the prompt.

B.

Choose an LLM of a different size.

C.

Increase the temperature.

D.

Increase the Top K value.

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Questions 7

What are tokens in the context of generative AI models?

Options:

A.

Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.

B.

Tokens are the mathematical representations of words or concepts used in generative AI models.

C.

Tokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.

D.

Tokens are the specific prompts or instructions given to a generative AI model to generate output.

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Questions 8

An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort.

Which strategy meets these requirements?

Options:

A.

Object detection

B.

Anomaly detection

C.

Named entity recognition

D.

Inpainting

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Questions 9

A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts.

An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders.

What should the AI practitioner include in the report to meet the transparency and explainability requirements?

Options:

A.

Code for model training

B.

Partial dependence plots (PDPs)

C.

Sample data for training

D.

Model convergence tables

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Questions 10

A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company needs the LLM to produce more consistent responses to the same input prompt.

Which adjustment to an inference parameter should the company make to meet these requirements?

Options:

A.

Decrease the temperature value

B.

Increase the temperature value

C.

Decrease the length of output tokens

D.

Increase the maximum generation length

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Questions 11

Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

Options:

A.

Calculate the total cost of resources used by the model.

B.

Measure the model's accuracy against a predefined benchmark dataset.

C.

Count the number of layers in the neural network.

D.

Assess the color accuracy of images processed by the model.

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Questions 12

A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.

Which type of model meets this requirement?

Options:

A.

Topic modeling

B.

Clustering models

C.

Prescriptive ML models

D.

BERT-based models

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Questions 13

A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.

Which solution will meet these requirements?

Options:

A.

Configure the security and compliance by using Amazon Inspector.

B.

Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.

C.

Encrypt and secure training data by using Amazon Macie.

D.

Gather more data. Use Amazon Rekognition to add custom labels to the data.

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Questions 14

A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.

Which solution will meet these requirements?

Options:

A.

Customize the model by using fine-tuning.

B.

Decrease the number of tokens in the prompt.

C.

Increase the number of tokens in the prompt.

D.

Use Provisioned Throughput.

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Questions 15

A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level.

Which solution will meet these requirements?

Options:

A.

Decrease the batch size.

B.

Increase the epochs.

C.

Decrease the epochs.

D.

Increase the temperature parameter.

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Questions 16

A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer.

What can Amazon Q Developer do to help the company meet these requirements?

Options:

A.

Create software snippets, reference tracking, and open-source license tracking.

B.

Run an application without provisioning or managing servers.

C.

Enable voice commands for coding and providing natural language search.

D.

Convert audio files to text documents by using ML models.

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Questions 17

A company has built a solution by using generative AI. The solution uses large language models (LLMs) to translate training manuals from English into other languages. The company wants to evaluate the accuracy of the solution by examining the text generated for the manuals.

Which model evaluation strategy meets these requirements?

Options:

A.

Bilingual Evaluation Understudy (BLEU)

B.

Root mean squared error (RMSE)

C.

Recall-Oriented Understudy for Gisting Evaluation (ROUGE)

D.

F1 score

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Questions 18

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?

Options:

A.

Pairs of chatbot responses and correct user intents

B.

Pairs of user messages and correct chatbot responses

C.

Pairs of user messages and correct user intents

D.

Pairs of user intents and correct chatbot responses

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Questions 19

A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket.

The data is encrypted with Amazon S3 managed keys (SSE-S3).

The FM encounters a failure when attempting to access the S3 bucket data.

Which solution will meet these requirements?

Options:

A.

Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.

B.

Set the access permissions for the S3 buckets to allow public access to enable access over the internet.

C.

Use prompt engineering techniques to tell the model to look for information in Amazon S3.

D.

Ensure that the S3 data does not contain sensitive information.

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Questions 20

A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VPC. To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic.

Which AWS service or feature will meet these requirements?

Options:

A.

AWS PrivateLink

B.

Amazon Macie

C.

Amazon CloudFront

D.

Internet gateway

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Questions 21

A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.

Which business objective should the company use to evaluate the effect of the LLM chatbot?

Options:

A.

Website engagement rate

B.

Average call duration

C.

Corporate social responsibility

D.

Regulatory compliance

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Questions 22

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).

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Questions 23

A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.

Which solution will meet this requirement?

Options:

A.

Use a different FM

B.

Choose a lower temperature value

C.

Create an Amazon Bedrock knowledge base

D.

Enable model invocation logging

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Questions 24

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.

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Questions 25

A company wants to display the total sales for its top-selling products across various retail locations in the past 12 months.

Which AWS solution should the company use to automate the generation of graphs?

Options:

A.

Amazon Q in Amazon EC2

B.

Amazon Q Developer

C.

Amazon Q in Amazon QuickSight

D.

Amazon Q in AWS Chatbot

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Questions 26

A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data.

Which solution will meet these requirements?

Options:

A.

Store the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.

B.

Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.

C.

Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.

D.

Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.

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Exam Code: AIF-C01
Exam Name: AWS Certified AI Practitioner Exam(AI1-C01)
Last Update: Oct 14, 2024
Questions: 87
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