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AIF-C01 Questions and Answers

Question # 6

Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team's VPC?

A.

Amazon Personalize

B.

Amazon SageMaker JumpStart

C.

PartyRock, an Amazon Bedrock Playground

D.

Amazon SageMaker endpoints

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Question # 7

An AI practitioner has built a deep learning model to classify the types of materials in images. The AI practitioner now wants to measure the model performance.

Which metric will help the AI practitioner evaluate the performance of the model?

A.

Confusion matrix

B.

Correlation matrix

C.

R2 score

D.

Mean squared error (MSE)

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Question # 8

An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.

What should the firm do when developing and deploying the LLM? (Select TWO.)

A.

Include fairness metrics for model evaluation.

B.

Adjust the temperature parameter of the model.

C.

Modify the training data to mitigate bias.

D.

Avoid overfitting on the training data.

E.

Apply prompt engineering techniques.

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Question # 9

A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.

Which solution meets these requirements?

A.

Optimize the model's architecture and hyperparameters to improve the model's overall performance.

B.

Increase the model's complexity by adding more layers to the model's architecture.

C.

Create effective prompts that provide clear instructions and context to guide the model's generation.

D.

Select a large, diverse dataset to pre-train a new generative model.

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Question # 10

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?

A.

Data pre-processing

B.

Feature engineering

C.

Exploratory data analysis

D.

Hyperparameter tuning

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Question # 11

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?

A.

Object detection

B.

Anomaly detection

C.

Named entity recognition

D.

Inpainting

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Question # 12

Which metric measures the runtime efficiency of operating AI models?

A.

Customer satisfaction score (CSAT)

B.

Training time for each epoch

C.

Average response time

D.

Number of training instances

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Question # 13

A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency.

Which SageMaker inference option meets these requirements?

A.

Real-time inference

B.

Serverless inference

C.

Asynchronous inference

D.

Batch transform

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Question # 14

A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology.

Which solution meets these requirements?

A.

Generative pre-trained transformers (GPT)

B.

Residual neural network

C.

Support vector machine

D.

WaveNet

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Question # 15

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?

A.

Code for model training

B.

Partial dependence plots (PDPs)

C.

Sample data for training

D.

Model convergence tables

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Question # 16

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?

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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Question # 17

Which option is a use case for generative AI models?

A.

Improving network security by using intrusion detection systems

B.

Creating photorealistic images from text descriptions for digital marketing

C.

Enhancing database performance by using optimized indexing

D.

Analyzing financial data to forecast stock market trends

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Question # 18

Which functionality does Amazon SageMaker Clarify provide?

A.

Integrates a Retrieval Augmented Generation (RAG) workflow

B.

Monitors the quality of ML models in production

C.

Documents critical details about ML models

D.

Identifies potential bias during data preparation

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Question # 19

An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images.

Which type of FM should the AI practitioner use to power the search application?

A.

Multi-modal embedding model

B.

Text embedding model

C.

Multi-modal generation model

D.

Image generation model

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Question # 20

A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.

Which ML algorithm meets these requirements?

A.

Decision trees

B.

Linear regression

C.

Logistic regression

D.

Neural networks

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Question # 21

A company is building an application that needs to generate synthetic data that is based on existing data.

Which type of model can the company use to meet this requirement?

A.

Generative adversarial network (GAN)

B.

XGBoost

C.

Residual neural network

D.

WaveNet

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Question # 22

A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data.

Which strategy will successfully fine-tune the model?

A.

Provide labeled data with the prompt field and the completion field.

B.

Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.

C.

Purchase Provisioned Throughput for Amazon Bedrock.

D.

Train the model on journals and textbooks.

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Question # 23

A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with multiple regulatory frameworks.

Which capabilities can the company show compliance for? (Select TWO.)

A.

Auto scaling inference endpoints

B.

Threat detection

C.

Data protection

D.

Cost optimization

E.

Loosely coupled microservices

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Question # 24

A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.

Which solution scope gives the company the MOST ownership of security responsibilities?

A.

Using a third-party enterprise application that has embedded generative AI features.

B.

Building an application by using an existing third-party generative AI foundation model (FM).

C.

Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.

D.

Building and training a generative AI model from scratch by using specific data that a customer owns.

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Question # 25

An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image generation and create bias in the model.

Which technique will solve the problem?

A.

Data augmentation for imbalanced classes

B.

Model monitoring for class distribution

C.

Retrieval Augmented Generation (RAG)

D.

Watermark detection for images

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Question # 26

A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.

The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.

Which solution will meet these requirements?

A.

Use Amazon SageMaker Serverless Inference to deploy the model.

B.

Use Amazon CloudFront to deploy the model.

C.

Use Amazon API Gateway to host the model and serve predictions.

D.

Use AWS Batch to host the model and serve predictions.

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