Font size
S
M
L
XL
WorksheetsAWS AI Practitioner - 1 até 25
Total questions: 25
Worksheet time: 25mins
Name
Class
Date
1.
A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.
Which action must the company take to use the custom model through Amazon Bedrock?
a)
Purchase Provisioned Throughput for the custom model.
b)
Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.
c)
Register the model with the Amazon SageMaker Model Registry.
d)
Grant access to the custom model in Amazon Bedrock.
2.
A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteria. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers.
Which actions should the company take to meet these requirements? (Choose two.)
a)
Detect imbalances or disparities in the data.
b)
Ensure that the model runs frequently.
c)
Evaluate the model's behavior so that the company can provide transparency to stakeholders.
d)
Use the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate.
e)
Ensure that the model's inference time is within the accepted limits.
3.
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.
4.
A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?
a)
User-generated content
b)
Moderation logs
c)
Content moderation guidelines
d)
Benchmark datasets
5.
A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files.
Which solution meets these requirements MOST cost-effectively?
a)
Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.
b)
Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.
c)
Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.
d)
Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.
6.
An ecommerce company wants to build a solution to determine customer sentiments based on written customer reviews of products.
Which AWS services meet these requirements? (Choose two.)
a)
Amazon Lex
b)
Amazon Comprehend
c)
Amazon Polly
d)
Amazon Bedrock
e)
Amazon Rekognition
7.
A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly.
What should the company do to mitigate this problem?
a)
Reduce the volume of data that is used in training.
b)
Add hyperparameters to the model.
c)
Increase the volume of data that is used in training.
d)
Increase the model training time.
8.
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
9.
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?
a)
Website engagement rate
b)
Average call duration
c)
Corporate social responsibility
d)
Regulatory compliance
10.
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?
a)
Decrease the batch size.
b)
Increase the epochs.
c)
Decrease the epochs.
d)
Increase the temperature parameter.
11.
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? (Choose two.)
a)
Auto scaling inference endpoints
b)
Threat detection
c)
Data protection
d)
Cost optimization
e)
Loosely coupled microservices
12.
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?
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.
13.
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?
a)
Use a different FM.
b)
Choose a lower temperature value.
c)
Create an Amazon Bedrock knowledge base.
d)
Enable model invocation logging.
14.
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
15.
A company built a deep learning model for object detection and deployed the model to production.
Which AI process occurs when the model analyzes a new image to identify objects?
a)
Training
b)
Inference
c)
Model deployment
d)
Bias correction
16.
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
17.
How can companies use large language models (LLMs) securely on Amazon Bedrock?
a)
Design clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access.
b)
Enable AWS Audit Manager for automatic model evaluation jobs.
c)
Enable Amazon Bedrock automatic model evaluation jobs.
d)
Use Amazon CloudWatch Logs to make models explainable and to monitor for bias.
18.
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
19.
A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.
Which Amazon Bedrock pricing model meets these requirements?
a)
On-Demand
b)
Model customization
c)
Provisioned Throughput
d)
Spot Instance
20.
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
21.
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.
22.
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.
23.
An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV's compliance reports become available.
Which AWS service can the company use to meet this requirement?
a)
AWS Audit Manager
b)
AWS Artifact
c)
AWS Trusted Advisor
d)
AWS Data Exchange
24.
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.
25.
A security company is using Amazon Bedrock to run foundation models (FMs). The company wants to ensure that only authorized users invoke the models. The company needs to identify any unauthorized access attempts to set appropriate AWS Identity and Access Management (IAM) policies and roles for future iterations of the FMs.
Which AWS service should the company use to identify unauthorized users that are trying to access Amazon Bedrock?
a)
AWS Audit Manager
b)
AWS CloudTrail
c)
Amazon Fraud Detector
d)
AWS Trusted Advisor
Reset
