scenario questions

A company that uses Amazon Bedrock for generating product descriptions wants to ensure that the output does not contain any confidential information from its proprietary database that is used as context. The company uses a knowledge base in Bedrock to augment the model. The security team is concerned that the model might inadvertently regurgitate exact strings from the knowledge base. The company wants to adopt a solution that prevents this while still allowing the model to use the knowledge base for generating relevant descriptions. What should the company do?

A company uses Amazon Bedrock with a custom model deployed via Amazon SageMaker. They want to monitor for data drift in input prompts over time. Which AWS service is best suited for this?

A financial services company is deploying a machine learning model to approve loans. They want to ensure that the model does not discriminate based on race or gender. Which AWS service or feature can help them detect bias in the model's predictions?

A company is building a multi-modal application that processes images and text to answer questions about product defects. Which foundation model approach is BEST?

Refer to the exhibit. You are trying to invoke a foundation model via Amazon Bedrock but receive this error. What should you do to resolve it?

A company runs a question-answering application on Amazon Bedrock that answers from a large knowledge base. Recently, users have reported that the model gives incomplete answers, often missing details from the middle of documents. The team suspects the chunking strategy is suboptimal. Which adjustment is MOST likely to improve completeness?

A company is developing a generative AI application using Amazon Bedrock for code generation. They want to reduce costs without sacrificing throughput. Which THREE approaches can help achieve cost optimization?

A company is deploying a generative AI application that creates marketing copy. They want to ensure the outputs do not include harmful or inappropriate content. Which AWS service can enforce content policies and filter undesirable outputs?

A developer is using the Amazon Bedrock API to generate text. They notice that the model sometimes returns harmful content despite setting safety parameters. What is the BEST way to add an additional layer of content filtering?

A company is designing a RAG pipeline for a legal document review system. They need to ingest hundreds of documents, create embeddings, and store them for retrieval. Which THREE steps are essential in the ingestion phase of the RAG pipeline?

Which Amazon Bedrock feature allows you to invoke a model and receive the response token by token as it is generated, reducing perceived latency for the end user?

A company wants to build a chatbot that responds to customer queries using a foundation model. They need low latency and want to avoid managing infrastructure. Which AWS service should they use?

A developer needs to ensure that a generative AI application on Amazon Bedrock does not produce harmful or inappropriate content. Which feature should they configure?

A company is using Bedrock Knowledge Bases with Amazon OpenSearch Serverless as the vector store. They need to ensure that the vector search returns results within 500ms for real-time queries. The current average latency is 800ms. Which change is MOST likely to reduce latency?

A company is building a chatbot using Amazon Bedrock. They want to ensure the model's responses are grounded in their internal knowledge base and avoid generating information outside that scope. Which feature should they use?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A data scientist is preparing a dataset for training a linear regression model. The dataset contains missing values and categorical features. Which TWO actions are appropriate to perform during data preprocessing? (Select TWO.)

A machine learning team uses Amazon SageMaker to train models. They need to ensure that only approved base models from the AWS Marketplace can be used, and that training jobs cannot access the internet. Which TWO configurations should they implement?

A company operates in a region where Amazon Bedrock is not available. They want to use generative AI but must keep data within the country. Which solution should they consider?

An organization uses AWS Lake Formation to govern a data lake used for SageMaker training. They need to enforce row-level security so that different teams only see data relevant to their projects. Which Lake Formation feature should they use?

A data scientist is using Amazon SageMaker to train a model with data that resides in an S3 bucket owned by another AWS account. The training job fails with access denied errors. The data scientist has already been granted cross-account read access to the S3 bucket via a bucket policy. What additional configuration is required?

A healthcare company is training a model on sensitive patient data using Amazon SageMaker. They need to ensure that individual patient data cannot be reverse-engineered from the model. Which technique should they implement during training?

A company is deploying a customer‑facing chatbot using Amazon Bedrock. They need to ensure the chatbot never reveals personally identifiable information (PII) and refuses to discuss the topic of 'employee salaries'. Which TWO Bedrock Guardrails features should they configure together? (Select TWO.)

A company is developing a speech-to-text application for a diverse user base. To ensure inclusive design, they test the model with different accents and dialects. They find that error rates are higher for certain accents. Which responsible AI principle is most directly violated?

A machine learning engineer wants to detect if sensitive data, such as personally identifiable information (PII), exists in a training dataset stored in S3 before training a model. Which AWS service should they use?

A company is using Amazon Bedrock to generate responses for customer support. They want to ensure that the model does not expose personally identifiable information (PII) in its outputs. Which AWS feature can be configured to automatically redact PII from model responses?

A company uses a Bedrock Agent to handle customer support tickets. The agent needs to look up order status from a legacy API that requires authentication. The agent should also escalate to a human if the query is not supported. Which combination of components should the developer configure?

A data scientist is using SageMaker to train a model on a dataset with many features. They suspect some features are redundant. Which feature engineering technique would help?

Refer to the exhibit. An IAM policy is attached to a user. Which models can the user invoke?

An organization uses Amazon Bedrock to generate content. They have implemented guardrails to block toxic content. However, some users are able to bypass the guardrails by encoding their prompts. What step should be taken to improve security?

A financial services company uses Amazon Bedrock to generate investment report summaries. They have strict compliance requirements that the model must not discuss certain topics like insider trading or unapproved financial advice. Which Bedrock feature should they use to deny these topics?

A practitioner is using Amazon Bedrock to invoke Anthropic Claude for a text generation task. They need the model to output a JSON object with specific keys, and they have observed that the model occasionally produces malformed JSON. Which parameter adjustment is MOST likely to improve JSON formatting consistency?

A data scientist fine-tuned a large language model on Amazon SageMaker for financial report generation. The model produces responses that are too short and incomplete, often cutting off mid-sentence. What parameter should be adjusted first?

A data scientist needs to grant an IAM user access to a specific Amazon SageMaker notebook instance. The user should only be able to start and stop the notebook instance, but not delete it. Which IAM policy statement should be used?

A company wants to send personalized product recommendations to customers based on their browsing history and previous purchases. Which AWS service is BEST suited for this?

A company is evaluating the output quality of a summarisation model using Amazon Bedrock Model Evaluation. They want to use both automated and human evaluation. Which THREE components can they configure as part of a model evaluation job? (Choose THREE.)

An organization wants to prototype a new generative AI application and allow multiple team members to collaborate on prompt engineering and model selection without writing code. Which tool should they use?

A company wants to use Amazon Bedrock to generate responses grounded in their proprietary knowledge base. They need to minimize hallucinations and ensure responses are based on the provided documents. Which feature should they enable?

A company deploys an Amazon Bedrock agent that uses a knowledge base with sensitive financial documents. The security team requires that all data retrieval queries be logged for auditing, and that the LLM responses do not contain any personally identifiable information (PII). What combination of services should the company use?

A financial services company is deploying a foundation model on Amazon Bedrock to generate compliance reports from internal audit logs. The model must not output any personally identifiable information (PII). They have configured a Bedrock Guardrail with sensitive information filters set to the 'HIGH' sensitivity level. During testing in a staging environment, testers still observed PII being occasionally generated in the report outputs. The guardrail did not block these instances because the PII was embedded in a context that the guardrail's pattern matching did not catch (e.g., structured JSON data with embedded names). The company requires a solution that minimizes latency and cost, as they process thousands of reports daily. They cannot afford to increase inference time significantly due to strict SLAs. They also want to avoid re-engineering the entire solution. Which additional step should they take to effectively eliminate PII leakage while maintaining performance?

Which TWO are best practices for model monitoring in production on AWS?

A healthcare AI system predicts patient diagnoses. The data collection process primarily samples from urban hospitals, leading to underrepresentation of rural populations. Which type of bias is this, and what is the most effective mitigation strategy?

Which AWS service provides a serverless experience for building and scaling generative AI applications with access to various foundation models?

A company wants to use Amazon Bedrock to generate images from text descriptions. Which model should they use?

A company needs to convert a large number of recorded customer service calls into text for analysis. Which AWS service should they use?

Refer to the exhibit. A data scientist ran a training job on Amazon SageMaker. The job failed with the error shown. What is the most likely cause?

A financial services company is deploying a generative AI model on Amazon SageMaker for real-time fraud detection. The model, a fine-tuned Llama 2 7B, must respond to transaction requests within 500 milliseconds. The team has deployed the model using a SageMaker real-time endpoint with a single ml.g5.2xlarge instance. During load testing, the endpoint achieves an average latency of 450 ms at 10 requests per second (RPS), but the latency spikes to over 2 seconds at 20 RPS. The team needs to maintain sub-500 ms latency at up to 50 RPS. The model is too large to fit on a single GPU, so they are using CPU instances. They considered using a larger instance type but want to minimize cost. What should the team do to meet the latency requirement cost-effectively?

A data scientist is using SageMaker Clarify to analyze a binary classification model for gender bias. The dataset has 80% male and 20% female applicants. The model predicts positive outcomes for 60% of males and 30% of females. Which fairness metric would directly capture this disparity in prediction rates?

A developer invoked an Amazon Bedrock model and received this output. What does the stopReason field indicate?

A company is using Amazon SageMaker Ground Truth to create labeled datasets for a computer vision model. The dataset contains images of people in public places. The company must comply with data privacy regulations that require explicit consent for using images of individuals. The company has a privacy team that reviews the images and provides consent lists. The ML team suspects that some images in the dataset might include individuals who have not consented. The company wants to ensure that only those images with consent are used for training. What should the company do?

According to AWS's responsible AI principles, which principle focuses on the idea that AI systems should produce consistent and reliable results even under unexpected conditions?

A data science team is using SHAP values to explain a complex model. They notice that for a particular prediction, the SHAP value for feature 'age' is +0.3. What does this indicate?

A developer is using Amazon Bedrock Agents to create an agent that can book meetings by interacting with a calendar API. They have defined an action group with an OpenAPI schema. What is required to execute the API call when the agent decides to use it?

Which TWO AWS services can be used to build a chatbot that responds to customer inquiries using a company's documentation as source? (Select two.)

A team is deploying a regression model for loan approval. To ensure transparency for regulators, they need to explain individual predictions. Which interpretability method can provide local explanations by approximating the model with a simpler surrogate?

Which TWO factors should be considered when choosing between a CPU-based instance and a GPU-based instance for training a machine learning model on Amazon SageMaker? (Choose two.)

A company is using Amazon Bedrock to generate code snippets. Developers report that the generated code sometimes contains security vulnerabilities. Which action should the team take to mitigate this risk?

A company is training a large language model using Amazon SageMaker. The training job fails with the error 'OutOfMemory'. They are using a single ml.p3.2xlarge instance. The dataset is 50GB and the model is 2GB. The training script uses standard data loading. Which action should they take to resolve the issue?

A developer needs to evaluate the quality of a text summarization model by comparing its output to reference summaries. Which automated metric measures the overlap of n‑grams between the generated and reference summaries?

A machine learning team uses SageMaker Clarify to evaluate a model for bias. The dataset includes a feature 'ZipCode' that correlates strongly with income and race. The team is concerned about proxy discrimination. What is the MOST effective way to address this in the context of responsible AI?

A company wants to use a foundation model to automatically moderate user-generated content. The model must filter out inappropriate content with high accuracy. Which Amazon service is best suited for this task?

A startup needs to build a real-time text translation feature for a customer chat application. Latency must be under 200 ms per request. Which AWS approach is BEST suited?

A developer is using Amazon Bedrock Agents to build a multi-step reasoning workflow. The agent needs to query an external REST API to fetch data. What must the developer define in the agent configuration?

A financial services company is deploying a machine learning model that must comply with SOC 2 and PCI DSS. They need to ensure that the model artifacts and training data are encrypted, access is audited, and the environment is protected from network threats. Which THREE AWS services should they implement?

A company has trained a model using Amazon SageMaker and stored the model artifacts in S3 with SSE-KMS encryption. The development team wants to grant cross-account access to the model artifacts so a partner can deploy the model in their own account. Which steps are required?

A company is building a chatbot using Amazon Bedrock. They want to ensure the model's responses are grounded in company-specific data and that harmful content is filtered out. Which two services or features should they use? (Choose TWO.)

A data scientist wants to deploy a custom model built with TensorFlow to Amazon SageMaker for real-time inference. Which TWO steps are required? (Choose two.)

A developer is using the Amazon Bedrock InvokeModel API with the above request to summarize meeting notes. The response is a single word repeated many times. Which parameter is MOST likely causing this issue?

A data scientist runs the SageMaker Clarify job shown in the exhibit for a credit risk model. After reviewing the results, they find a high bias metric for the gender facet. Which action is most consistent with responsible AI?

A startup wants to build a product recommendation engine for their e-commerce platform. They have user purchase history and item metadata. They want a fully managed solution that can automatically train and deploy a recommendation model without needing to manage the underlying ML lifecycle. The solution should provide personalized recommendations based on collaborative filtering. Which AWS service should they use?

A financial institution is developing a model to detect fraudulent transactions. They want to ensure the model is robust and does not exhibit bias. Which TWO actions should they take?

A data science team is developing a credit scoring model and wants to ensure it meets fairness requirements. They measure the model's disparate impact and find it exceeds the 80% rule (adverse impact ratio >0.8). Which THREE actions should they consider to mitigate this? (Choose three.)

A social media company deploys a content moderation model. They want to minimize the risk of over-censoring legitimate posts (false positives) while still catching harmful content. Which metric should they prioritize?

A data scientist wants to quickly experiment with a pre-trained LLM for text generation without writing any code. Which AWS service is MOST suitable?

A company uses Amazon Rekognition to detect objects in images. The model is producing a high number of false positives for a specific category. Which action should be taken to improve the model's precision for that category?

A company is deploying a large language model (LLM) for customer support. They want to reduce the risk of hallucinations. Which TWO approaches should they implement? (Choose two.)

A data scientist is training a binary classification model to predict customer churn. The dataset has 10,000 records with 9,500 non-churners and 500 churners. After training a logistic regression model, the model achieves 95% accuracy on the test set. However, the business team reports that the model is not useful because it predicts almost all customers as non-churners. Which metric should the data scientist use to evaluate the model's performance in this scenario?

A developer is using Amazon Bedrock to generate product descriptions. The developer notices that the model sometimes outputs descriptions that contradict the provided product specifications. Which parameter adjustment would MOST directly reduce factual inconsistencies?

A healthcare company needs to use Amazon SageMaker Ground Truth for data labeling. The data includes protected health information (PHI) that must remain in the US. Which configuration meets the compliance requirements?

A media company is using Amazon Bedrock to generate captions for images. They have a batch processing pipeline that sends thousands of images daily to the Bedrock API using the Titan Image Generator G1 model. Recently, they started receiving ThrottlingException errors during peak hours. The team needs to process all images within 24 hours without changing the model or the application code. The current account has a default quota of 10 requests per second (RPS) for the Titan model in us-east-1. The team estimates they need 50 RPS during peak hours. They have already implemented exponential backoff in the client, but the errors persist. What is the MOST effective solution to resolve the throttling issue?

A startup is using Amazon Bedrock to power a virtual assistant. They need to ensure that personally identifiable information (PII) is not included in the model's responses. Which feature should they enable?

A developer is building an application that generates product descriptions from images using a multimodal model. Which AWS service provides access to multimodal foundation models?

A machine learning engineer wants to ensure that a SageMaker notebook instance only has access to a specific S3 bucket containing training data. The notebook instance is in a VPC. What is the most secure way to restrict access?

A financial services company needs to use a foundation model for sensitive data analysis. They require that all data remains within a VPC and no data leaves the AWS network. Which solution should they choose?

A company deployed a chatbot using Amazon Lex integrated with a Lambda function that invokes Claude on Amazon Bedrock. The Lambda function retrieves relevant documents from an Amazon Kendra index to use as context. Users report that the chatbot's responses are often irrelevant or incorrect despite the Kendra index containing accurate information. The logs show that the Lambda function is correctly passing retrieved documents to the model. What is the most likely cause and solution?

A security team is concerned about adversarial attacks on their image classification model deployed on Amazon SageMaker. They want to test robustness against carefully crafted inputs that cause misclassification. What approach should they use?

A company is building a generative AI application using Amazon Bedrock and needs to ensure that the model does not generate outputs containing personally identifiable information (PII). Which TWO actions should the company take? (Choose 2)

A company wants to use a large language model to generate code based on natural language descriptions. They need to minimize latency and control costs by running inference on their own infrastructure. Which approach is most suitable?

Refer to the exhibit. A data scientist runs an Amazon SageMaker Clarify bias analysis on a binary classifier. The pre-training ClassImbalance is 1.5 and the post-training DPPL is 0.15. What should the data scientist conclude?

Refer to the exhibit. You receive this response from Amazon Bedrock. What is the most likely cause of the incomplete information?

An organization wants to control which topics their AI chatbot can discuss. For example, they want to block all conversations about investment advice. Which Amazon Bedrock Guardrails feature should they configure?

A company is using Amazon SageMaker to train machine learning models on sensitive customer data. Which AWS service can be used to encrypt the data at rest in the S3 bucket used by SageMaker?

A hospital is deploying an AI system to assist in diagnosing diseases from medical images. According to the EU AI Act, this system may be classified as high-risk. Which THREE requirements should the hospital address to comply with the EU AI Act for high-risk AI systems?

A social media platform uses an AI system to moderate content. They want to ensure that human reviewers can review decisions when the AI is uncertain. Which AWS service can be used to set up a human review workflow for AI predictions?

Refer to the exhibit. A developer wants to ensure the notebook instance can access the internet to download packages. Which property configuration ensures this?

Which TWO of the following are benefits of using Amazon Bedrock for building applications with foundation models?

A data scientist is training a model using Amazon SageMaker and notices the training loss is decreasing but validation loss starts increasing after a few epochs. Which technique should they apply to address this?

A company is using Amazon Bedrock to generate product descriptions. They notice that the model sometimes produces descriptions that contain factual errors about the products. Which TWO actions should they take to improve factual accuracy?

A company is deploying a generative AI model on Amazon Bedrock and needs to monitor for potential misuse. Which THREE measures should they implement? (Choose 3)

A company uses Amazon Bedrock and wants to ensure that the model outputs are grounded in a set of provided documents to reduce hallucinations. Which TWO actions should they take? (Select TWO.)

Which prompt engineering technique involves providing the model with a few examples of desired input-output pairs before asking it to complete a new instance?

A developer is building a RAG-based Q&A bot with Amazon Bedrock Knowledge Bases. They need a managed vector store for document embeddings. Which service should they use?

A company is building a chatbot using Amazon Bedrock and wants to ensure that the model generates responses consistent with its brand voice. Which technique should be used to provide the model with examples of desired responses without fine-tuning the model?

An e-commerce company stores user interaction logs in Amazon S3. They want to use machine learning to segment users based on purchasing behavior. Which unsupervised learning algorithm is most appropriate?

A financial services company is subject to strict regulatory requirements. They plan to use generative AI to summarize customer interaction logs. Which combination of AWS services and configurations best ensures compliance while maintaining accuracy?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A team trains a model using Amazon SageMaker built-in XGBoost. After training, they want to evaluate feature importance. Which SageMaker feature allows them to view this?

A healthcare company needs to use a foundation model for analyzing medical records while complying with HIPAA. They plan to use Amazon Bedrock. What should they do to meet HIPAA requirements?

A company wants to evaluate the quality of a text generation model for a summarization task. They have reference summaries written by humans. Which automated metric compares the generated summary to the reference by measuring n-gram overlap?

A retail company wants to generate product descriptions from catalog data. The data includes structured attributes (e.g., price, brand) and unstructured reviews. The team needs to ensure factual accuracy. Which approach is most appropriate?

A company wants to build an ML model to predict customer lifetime value. The dataset includes numerical features (age, income) and categorical features (gender, region). Which TWO preprocessing steps should be applied to the categorical features before training a linear regression model? (Choose TWO.)

A data scientist is using Amazon SageMaker Studio. The company policy requires that all data used in SageMaker Studio notebooks be encrypted at rest and in transit. Which configuration should be enabled to meet this requirement?

A company uses SageMaker Clarify to detect bias in a deployed model. The monitoring must run automatically on a schedule. Which SageMaker feature should they use?

A startup uses Amazon Lex to build a chatbot for mental health support. They must ensure user conversations are private and not used for model improvement. Which AWS service can help anonymize text data before storage?

A company uses Amazon SageMaker to build and deploy machine learning models. The security team has implemented a policy that all SageMaker notebook instances must be launched in a VPC and cannot have direct internet access. However, data scientists need to download open-source datasets from the internet for model training. They also need to install Python packages from PyPI. Currently, the SageMaker notebook instances are in a VPC with no internet gateway. The data scientists cannot download any external data or packages. The VPC has a NAT gateway already configured. What should the company do to allow the necessary internet access while maintaining the security requirement?

A company uses Amazon Bedrock to generate product descriptions. They need to ensure outputs do not contain offensive language. Which service should they integrate to filter content?

Which TWO practices help ensure transparency in AI systems? (Choose 2)

A company wants to automatically detect and redact personally identifiable information (PII) from customer support transcripts. Which TWO AWS services can be used together to achieve this? (Choose two.)

A company is building a customer support chatbot using Amazon Bedrock. They need to store conversation history for context across sessions. Which AWS service is best suited for this purpose?

What is the primary purpose of a model card?

A company uses Amazon SageMaker Clarify to monitor a deployed model for bias. After running an analysis, they find that the model's predictions have a disparate impact on a protected group. What is the MOST appropriate next step?

A company uses Amazon SageMaker Model Registry to manage model versions. The security team requires that only approved models can be deployed to production. The ML team creates a new model version and registers it in the Model Registry. When trying to deploy the model to a production endpoint, the deployment fails because the model is not approved. The ML team asks the DevOps team to approve the model. However, the DevOps team cannot see the model in the Model Registry. What is the MOST likely reason?

A company deployed a question-answering system using Amazon Bedrock with a knowledge base (RAG). Users report that the model often hallucinates facts not in the knowledge base. What is the most effective way to reduce hallucinations?

A company is building a generative AI application for code generation. They want to minimize costs while maintaining acceptable performance for their workload, which has periodic spikes in demand. Which approach would be MOST cost-effective?

A financial institution is building a model to approve loan applications. They must comply with the EU AI Act, which classifies credit scoring as a high-risk AI system. Which requirement is the MOST likely to apply under the EU AI Act?

A financial services company uses Amazon Bedrock to generate investment advice. They have configured a guardrail to deny any harmful content. However, a user prompt 'Tell me how to commit fraud' was not blocked. What is the most likely cause?

A company wants to ensure that only approved machine learning models are deployed to production on Amazon SageMaker. Which combination of services can enforce this governance requirement?

A security engineer creates the above IAM policy to allow a user to invoke an Amazon Bedrock model. However, invocation fails. What is the issue?

A company uses Amazon Bedrock to build an AI assistant. They need to restrict the model from generating responses about competitors. Which Bedrock feature should they configure?

A company wants to personalize product recommendations for its e-commerce website. The recommendation engine should adapt to each user's browsing and purchase history in real time. Which AWS service is MOST suitable?

A company uses Amazon Bedrock Agents to automate a multi-step data processing workflow. The agent needs to call an external API to enrich customer records. How should the developer expose this API to the agent?

A model trained to predict credit risk shows that applicants from a certain zip code are disproportionately rejected, even though income and credit history are comparable. Which type of bias is MOST likely present?

A financial services company uses Amazon SageMaker to train models with sensitive customer data. They must ensure that no data leaves a specific AWS Region due to data residency regulations. The training data is in S3. Which architecture meets this requirement while minimizing data transfer?

Which AWS service provides managed foundation models from providers like Anthropic, Meta, and Stability AI through a single API?

A data scientist is preparing data for a classification model. The dataset contains missing values in several features. Which TWO approaches are appropriate for handling missing data? (Select TWO.)

A financial services company needs to ensure that the machine learning models used for loan approval are explainable and meet regulatory compliance. Which AWS feature can help explain model predictions?

Which TWO techniques can reduce the cost of running a fine-tuned foundation model on Amazon SageMaker? (Choose TWO.)

An organization wants to document key information about their machine learning model, including intended use, performance metrics, training data, and ethical considerations. Which tool or practice should they adopt?

A company needs to select a vector store for their Amazon Bedrock Knowledge Base. Which TWO options are supported as vector stores? (Choose TWO.)

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A healthcare organization is developing a clinical decision support system using Amazon Bedrock with a large language model (LLM) to analyze patient symptoms and suggest potential diagnoses. The system must comply with HIPAA and internal responsible AI guidelines. During testing, the model occasionally generates diagnoses that are inconsistent with established medical guidelines and shows a tendency to recommend more aggressive treatments for patients from certain demographic groups. The team has already implemented data encryption, access controls, and basic content filtering. They need to further reduce biased and unsafe outputs without delaying the deployment timeline. What should the team do next?

A data scientist needs to restrict access to a SageMaker notebook instance to only the corporate network. Which configuration should they use?

A machine learning engineer notices that the training loss decreases steadily, but the validation loss starts increasing after a few epochs. Which of the following is the MOST likely cause?

A company wants to detect sensitive data such as PII in their training datasets stored in S3 before using them for model training. Which AWS service should they use?

A company uses Amazon Rekognition to analyze images stored in an S3 bucket. The security team requires that all image analysis be logged to AWS CloudTrail for auditing. What is the minimum configuration needed to meet this requirement?

A healthcare organization uses an ML model to predict patient readmission risk. To comply with regulations, they need to explain individual predictions to clinicians. Which explainability technique provides local, model-agnostic explanations that are computationally efficient?

A company wants to build a model to forecast monthly sales. The data is a time series with trend and seasonality. Which SageMaker algorithm is most appropriate?

A startup is building an AI-powered code assistant using a large language model (LLM). They want to ensure the model generates syntactically correct code and avoids security vulnerabilities. Which technique should they prioritize?

A company is deploying a machine learning model for real-time fraud detection. The model must make predictions with latency under 10 milliseconds. The data scientist trained a gradient boosting model that achieves high accuracy but has inference latency of 50 milliseconds. The team has access to a larger instance type with more CPU cores. Which approach should the data scientist take to reduce inference latency while maintaining accuracy?

A data scientist sets up a Model Monitoring schedule for data quality. What is a potential security issue with this configuration?

A company wants to use Amazon Bedrock to build an application that summarizes customer support tickets. They are concerned about data privacy and want to ensure that customer data is not used by the third-party model provider for training or improvement. Which TWO actions should they take?

An e-commerce company is building a product description generator using Amazon Bedrock. They want to ensure that the generated descriptions do not include any prohibited content (e.g., offensive language or competitor mentions). The company has a list of denied topics and keywords. Which feature should they use?

A company uses Amazon SageMaker Pipelines for MLOps. The security team requires that all pipeline steps use only approved Docker images from a private Amazon ECR repository, and that all pipeline artifacts are encrypted with a customer managed KMS key. Which THREE steps must the company configure to meet these requirements? (Choose three.)

A company is using Amazon Bedrock to deploy a generative AI application. They want to implement guardrails to prevent the model from generating harmful or offensive content. Which feature of Bedrock Guardrails should they configure?

A company uses Amazon SageMaker to host a real-time inference endpoint. The model was trained on sensitive data, and the company wants to ensure that the data sent to the endpoint is encrypted in transit. Additionally, the company wants to restrict access to the endpoint to only traffic originating from a specific VPC. Which configuration meets these requirements?

A developer is building an application that translates customer support tickets from English to Spanish using Amazon Bedrock. They need to evaluate the quality of translations. Which automated metric is most appropriate for comparing the model's translations to professional human translations?

A team is training a binary classification model using Amazon SageMaker. They notice that the training accuracy is 99% but the test accuracy is only 70%. Which technique should they apply first to address this?

A healthcare startup is building a patient inquiry system using Amazon Bedrock. They must ensure the model does not generate responses containing medical advice or unverified treatment suggestions. The compliance team also requires that no personally identifiable information (PII) is output. Which Bedrock feature should the startup configure to meet both requirements?

A company uses Amazon Bedrock to generate product descriptions. They notice that the model sometimes produces factually incorrect information. They want to ensure responses are grounded in company-provided documents. Which Bedrock feature should they enable?

A developer wants to store and search vector embeddings for a RAG application. Which AWS-managed vector store option is serverless and can be used with Amazon Bedrock?

A company uses an AI system to automate loan approvals. The model uses demographic features and achieves high accuracy, but the company wants to ensure compliance with responsible AI guidelines. Which practice best balances performance and fairness?

A financial services company uses Amazon Bedrock Knowledge Bases to power a Q&A bot for analysts. They notice that the bot sometimes gives outdated information because documents are updated weekly. They cannot retrain or rebuild the knowledge base weekly. What is the MOST efficient solution?

A financial institution uses Amazon SageMaker to host a model for credit scoring. The model was trained on data that includes demographic attributes. During a routine audit, the compliance team finds that the model produces significantly different approval rates for applicants of different ethnicities, even when credit profiles are similar. The institution must continue using the model but needs to ensure compliance with fair lending laws. What should the company do FIRST?

A team is using a prompt engineering technique where they provide a few examples of desired input-output pairs in the prompt to guide the model's response. Which technique are they using?

A company wants to use Amazon SageMaker to train a model using a custom Docker container that has specific dependencies. The training code is stored in an S3 bucket. Which steps must be taken to run the training job?

A security analyst is reviewing CloudTrail logs for SageMaker API calls to identify which user executed a particular training job. The logs show assumed roles. In which CloudTrail event field can the analyst find the name of the user who assumed the role?

A data scientist is evaluating different AWS services for building a machine learning pipeline. Which THREE components are part of Amazon SageMaker? (Select THREE.)

A company is using Amazon Comprehend for sentiment analysis on customer reviews. They notice that the sentiment is often incorrect for negative reviews with sarcasm. What is the likely cause?

A marketing team is using a foundation model to generate marketing copy. Which THREE of the following should they consider to ensure responsible and cost-effective use?

A company is using a foundation model on Amazon Bedrock to generate customer support responses. They notice that the model sometimes produces harmful or offensive content. Which approach is MOST effective to mitigate this issue?

A company is developing a generative AI application for content creation. They want to ensure transparency as per responsible AI guidelines. Which THREE practices should they implement? (Choose three.)

A company is building a generative AI application to answer questions from a large set of technical manuals. Which TWO services or features can be used together in a RAG architecture on AWS? (Choose TWO.)

An organization wants to detect anomalies in real-time streaming data from IoT devices. The data includes sensor readings, and the team plans to use a machine learning model. Which AWS service should be used to build and deploy the model with minimal operational overhead?

A company is deploying an AI model on Amazon SageMaker and needs to monitor for model drift over time. Which TWO actions should they take? (Choose TWO)

A company is developing an LLM-powered application that generates investment advice. They are concerned about the model producing inaccurate or fabricated information. Which combination of techniques should they implement to minimize hallucinations?

A company is developing an AI system that screens job applications. To comply with regulatory requirements, they need to provide explanations for each automated decision. Which explainability technique provides global feature importance across the entire dataset?

A company is using Bedrock Agents to automate multi-step workflows that interact with external APIs and databases. They need to ensure the agent can perform actions like querying a database and calling an API. Which TWO components must be defined to enable these capabilities? (Choose TWO)

A company uses Bedrock Guardrails to filter harmful content in a generative AI application. They need to prevent the model from discussing proprietary internal projects. Which Guardrail component should be configured?

A company uses Amazon Bedrock to build a question-answering system. Which THREE features of Amazon Bedrock can improve answer accuracy? (Choose three.)

A data scientist is using Amazon SageMaker to train a deep learning model for image classification. The training job is taking too long. The dataset consists of 100,000 images stored in Amazon S3. Which action can the data scientist take to reduce training time without modifying the model architecture?

A financial services firm is deploying a generative AI chatbot using Amazon Bedrock. They must ensure that the chatbot does not generate investment advice and that it automatically redacts any personally identifiable information (PII) from user inputs before processing. Which TWO Bedrock features should they use?

A company uses Amazon Bedrock with a third-party foundation model. They are concerned about the third-party provider accessing their data. What should they review to understand data handling practices?

A hospital uses an AI system to prioritize patients for organ transplant based on predicted survival rates. The system was trained on historical data that includes socioeconomic factors. A review reveals that the system systematically assigns lower priority to patients from lower-income neighborhoods, even when medical urgency is similar. The hospital's ethics board demands an immediate remedy. The data science team is small and must act quickly. What should the hospital do to address this fairness issue most effectively?

A data scientist is building a RAG application using Amazon Bedrock Knowledge Bases. The team requires that responses only use information from the uploaded documents and reject queries that are not related to the documents. Which Bedrock feature should be used to enforce this?

A company uses Amazon Bedrock Agents to process user requests that involve multiple steps, such as checking inventory and placing an order. The Agent sometimes fails to complete the workflow because it makes incorrect assumptions about the order of steps. What is the MOST effective way to guide the Agent's reasoning?

A company is building a chatbot using Amazon Bedrock. They want to provide up-to-date information from a continuously changing database. Which TWO services can be used as a data source for a Bedrock knowledge base? (Select TWO.)

A data science team is deploying a model using Amazon SageMaker. They need to monitor the model for bias after it is deployed. Which AWS service or feature should they use?

A marketing firm uses Amazon Bedrock to generate ad copy. They notice that the generated text often includes factual inaccuracies about their products. Which technique would most effectively reduce these inaccuracies?

A company operates a customer support chatbot that uses Amazon Bedrock with a knowledge base sourced from an S3 bucket containing frequently updated product documentation. The knowledge base uses OpenSearch Serverless as the vector store and is configured to sync daily. The chatbot uses the RetrieveAndGenerate API with a custom Lambda function that applies a system prompt instructing the model to base answers solely on the retrieved context. After a major update to the product documentation, the IT team verifies that the data source sync completed successfully and the new chunks are present in the OpenSearch index. However, the chatbot continues to respond with outdated information. Further investigation reveals that the Lambda function includes a response caching mechanism using Amazon ElastiCache for Redis with a Time-To-Live (TTL) of 24 hours. The cache key is based on the user query. The team notes that no cache invalidation is performed after documentation updates. What is the most likely cause of the outdated responses?

A healthcare company uses Amazon SageMaker to train a model on patient data. To meet HIPAA compliance, they must ensure training data is encrypted at rest and in transit. Additionally, the training job should not have internet access. Which combination of actions should the company take?

A data science team is using Amazon SageMaker to build a model. They want to ensure that only authorized users can deploy models to production. Which TWO methods can they use to enforce this?

A company uses Amazon Bedrock with a custom model that was trained on data subject to GDPR. The company needs to ensure that inference logs containing user prompts and model responses are stored in a specific AWS Region for data residency compliance. How should they configure Bedrock model invocation logging?

A company wants to encrypt training data stored in Amazon S3 and model artifacts in Amazon SageMaker using customer-managed keys. Which TWO AWS services or features should they use? (Select TWO.)

A media company is using Amazon Bedrock to generate marketing copy with a foundation model. They want to ensure the output adheres to brand voice guidelines (e.g., friendly, professional). Which prompt engineering strategy is most effective for this requirement?

A data scientist at a retail company is tasked with building a model to predict customer churn. The dataset contains 100,000 records with features such as age, purchase history, customer support interactions, and a binary label indicating whether the customer churned in the past. The team needs a model that can be deployed for real-time inference with low latency. They have limited time and want to use a built-in algorithm from Amazon SageMaker that is optimized for classification tasks. Which approach should they take?

A financial services company uses Amazon SageMaker Feature Store to manage features for machine learning models. The compliance auditor requires that all changes to feature definitions are logged and that feature data is immutable once written. Which TWO approaches should the team implement? (Choose two.)

A company needs to govern the lifecycle of ML models, including versioning, monitoring for drift, and decommissioning outdated models. Which TWO services should they use? (Choose 2)

A company is using Amazon Bedrock to deploy a chatbot. They want to ensure that the chatbot does not produce harmful or biased content. Which TWO AWS services or features can be used together to implement content moderation and monitoring?

A healthcare company uses Amazon Bedrock to generate patient summaries. They need to ensure no protected health information (PHI) is leaked in the output. Which AWS service can they use to detect and mask PHI in text?

A healthcare startup deploys a model to predict patient readmission risk using Amazon SageMaker. After deployment, the model shows higher false-positive rates for a specific age group. What is the most responsible first step?

An AI practitioner is deploying a large language model (LLM) for a customer support application. They are concerned about hallucinations, where the model generates plausible but incorrect information. Which combination of techniques would be MOST effective to mitigate hallucinations?

A startup needs to generate product descriptions from bullet points using a foundation model. They want a fully managed serverless experience. Which AWS service should they use?

A company wants to automatically discover sensitive data such as credit card numbers in their Amazon S3 training datasets before using them for model training. Which AWS service should they use?

Which TWO of the following are examples of supervised learning tasks that can be performed using Amazon SageMaker built-in algorithms?

A data science team needs to grant a SageMaker notebook instance access to an S3 bucket containing training data. Which IAM policy should be attached to the notebook instance's execution role?

A company wants to use a pre-trained generative AI model to analyze customer feedback. They need to adjust the model for their specific domain without retraining from scratch. Which approach is MOST suitable?

A company is using Amazon Bedrock to generate images. They want to ensure the outputs comply with content policies. Which TWO AWS services can help? (Choose two.)

A data scientist wants to detect potential bias in a binary classification model before deployment. Which AWS service can analyze the model's predictions across different demographic groups?

A company wants to deploy a real-time inference endpoint for a custom model on SageMaker. The model has high latency (100ms) and they need to handle variable traffic with spikes. Which deployment strategy is most cost-effective?

A company is building a customer service chatbot using Amazon Bedrock. Which component of a foundation model determines the creativity and randomness of the generated responses?

A healthcare startup is using Amazon Bedrock to generate clinical notes. They must prevent the model from outputting any personally identifiable information (PII) such as patient names. What is the most effective approach?

An AI system is used to detect fraudulent transactions. The system has a high false positive rate for a certain demographic group. To ensure fairness and reduce false positives, which mitigation strategy should be considered?

A company uses Amazon Bedrock to access foundation models. The security team wants to ensure that only specific IAM roles can invoke a particular model. Which configuration should they use?

Which of the following is a benefit of using cross-validation during model training?

During model training, the loss decreases rapidly for the first few epochs and then plateaus. The validation loss starts increasing after some epochs. What should the team do to improve generalization?

An insurance company is using a machine learning model to approve claims. They want to ensure that the model's approval rate is similar across different demographic groups. Which fairness metric would directly measure whether the proportion of positive outcomes is equal across groups?

Which TWO of the following are best practices for data preprocessing in machine learning? (Select TWO.)

A data scientist needs to allow a foundation model in Amazon Bedrock to access a specific S3 bucket containing reference documents. The bucket is in a different AWS account. What is the MOST secure way to grant access?

A multinational corporation uses a foundation model via Amazon Bedrock to translate internal communication documents from English to multiple languages. They notice that the translations often miss company-specific jargon and acronyms, leading to confusion. The company has a glossary of approved translations for terms like 'Project Atlas' and 'Operation Synergy.' They want to improve translation accuracy quickly and with minimal effort. What approach should they take?

A developer is using Amazon Bedrock to generate text summaries. The output sometimes includes irrelevant information. What is the most effective prompt engineering technique to improve relevance?

A developer is building an agent using Amazon Bedrock Agents to automate a multi-step workflow that involves querying several databases and APIs. The agent needs to handle intermediate results and decide the next step based on previous outputs. Which capability of Bedrock Agents enables this?

A machine learning team needs to share a trained model with multiple teams across different AWS accounts. The model artifacts are stored in an S3 bucket in the central account. What is the most secure way to grant cross-account read access to the model artifacts?

A company uses AWS Lake Formation to govern data used for AI/ML. They have a data lake containing customer transaction data. A data scientist needs to access the data for training a model in SageMaker. Which TWO steps are required to grant access while maintaining governance?

A developer wants to create an agent using Amazon Bedrock Agents that can call an external API to check inventory levels. What must be defined in the agent configuration to enable this API call?

A data scientist is fine-tuning a foundation model on SageMaker. They want to prevent overfitting. Which THREE actions can help? (Select THREE.)

A data scientist is setting up a RAG pipeline using Amazon Bedrock Knowledge Bases. They need to ingest documents, split them into chunks, generate embeddings, and store them for retrieval. Which TWO steps are part of the ingestion process? (Choose TWO)

A data governance team wants to enforce fine-grained access control on data in an Amazon S3 data lake used by multiple business units for AI training. Which AWS service should they use to define and manage data permissions at the table and column level?

Refer to the exhibit. A team is configuring a SageMaker Model Bias job. The baseline job has been completed. However, the bias job fails with a resource not found error. What is the most likely cause?

An organization uses a third-party foundation model accessed through Amazon Bedrock. The compliance team requires that all model inputs and outputs be auditable and retained for one year. Which approach should the team implement?

A team is evaluating two generative AI models for a summarization task. They have reference summaries and generated summaries. Which automated metric is BEST suited to measure the overlap of n-grams between the generated and reference summaries?

A financial services company uses a foundation model for document analysis. They need to ensure the model does not output sensitive customer information from its training data. What is the most effective mitigation?

A company uses a diffusion model on Amazon Bedrock to generate marketing images. They notice that the generated images often contain artifacts and lack fine details, especially when the prompt is complex. The team wants to improve image quality without increasing inference time significantly. Which parameter adjustment is MOST likely to help?

A company has deployed a model on Amazon SageMaker and enabled Model Monitor. They notice that the model's prediction accuracy has declined over time. Which type of drift is this, and what should they do?

A data scientist is comparing two foundation models for a text classification task. They want to use automated metrics to evaluate performance on a labelled test set. Which metric is most appropriate for a multi-class classification problem?

A bank is deploying a credit scoring model and must comply with regulatory requirements that decisions can be explained to customers. The model is a gradient boosting machine with hundreds of features. Which explainability technique should the team use to provide local explanations for individual loan decisions?

Which AWS service can be used to extract text and data from scanned documents such as invoices and receipts?

A data scientist is building a text classification system using Amazon Bedrock. They want to evaluate different foundation models for accuracy and latency. Which TWO approaches are appropriate for comparing models? (Select TWO.)

A company is using Amazon Bedrock to deploy a foundation model. To comply with GDPR, they need to ensure that the model does not generate outputs containing personally identifiable information (PII). Which AWS service can best help detect and redact PII from the model's responses?

A data scientist wants to perform automatic model tuning (hyperparameter optimization) on SageMaker. They need to find the best hyperparameters for a gradient boosting model. Which strategy is BEST for this task?

A startup is fine-tuning a large language model (LLM) for code generation using Amazon SageMaker. They are using a p4d.24xlarge instance with a single GPU. The training process is extremely slow, taking over 48 hours for one epoch. The dataset is 10GB of code snippets. The company needs to iterate quickly. Which action would most significantly reduce training time without sacrificing model quality?

Which THREE are best practices for ensuring generated content complies with corporate brand guidelines when using Amazon Bedrock?

A company is deploying an LLM for generating marketing copy. They want to reduce the risk of hallucinations and ensure the content is factually accurate. Which TWO approaches should they implement?

A company fine-tunes a foundation model on SageMaker using a custom dataset. They notice the training job takes too long. Which optimization technique is specifically designed to reduce training time for foundation models?

A company is using Amazon Bedrock to generate marketing content. They want to evaluate the quality of the generated text. Which TWO metrics are most appropriate for evaluating text quality?

A data scientist needs to train a model in Amazon SageMaker using a dataset that contains personally identifiable information (PII). The company policy requires all data at rest to be encrypted with a customer-managed key. Which configuration meets this requirement?

A financial services company needs to deploy a real-time fraud detection model with sub-100ms inference latency. The model is a large ensemble requiring 8 GB of memory per request. The workload has bursty traffic. Which Amazon SageMaker deployment strategy best meets these requirements?

A developer sends the above request to Amazon Bedrock with Anthropic Claude. The model returns a response that stops before reaching 500 tokens. What is the most likely reason?

Which of the following is a key principle of inclusive design in AI?

A company uses Amazon SageMaker for model training. To comply with data residency requirements, they must ensure that the training data never leaves a specific AWS region. However, during training, the SageMaker service might use resources in other regions for auto-scaling. Which configuration should they use to enforce data residency?

A data scientist is preparing to fine-tune an Amazon Titan model for a domain-specific text classification task. Which THREE components are essential for the fine-tuning process on Amazon Bedrock? (Choose THREE.)

A company is using Amazon Textract to extract text from scanned documents stored in an S3 bucket. The security team requires that all access to the documents be logged and that the documents be encrypted at rest using a customer-managed key. What should the company do to meet these requirements?

A data science team is fine-tuning a foundation model on Amazon SageMaker. Which THREE steps are part of the best practice? (Choose three.)

A developer implements a RAG pipeline with Amazon Bedrock and Amazon OpenSearch Serverless. Users report that the chatbot sometimes returns off-topic responses. Investigation shows the retrieved chunks are semantically unrelated to the queries. What is the MOST likely cause?

An e-commerce company uses Amazon Bedrock to generate product descriptions. They notice the descriptions are too long and contain repetitive phrases. Which parameter adjustment can help?

A research organization is using Amazon SageMaker Studio to collaborate on building machine learning models. The security policy requires that all data and code remain within a VPC and cannot be accessed from the public internet. Additionally, the organization wants to enforce that only approved base images are used for the Studio environment. How should the organization configure SageMaker Studio to meet these requirements?

A team is building an AI chatbot that will be used by customers with visual impairments. Which design practice best supports inclusive accessibility for this user group?

A company runs a chatbot using a large language model on Amazon Bedrock. They notice high latency during peak hours. Which action would be MOST effective to reduce latency without degrading response quality?

A data scientist is building a binary classifier to predict customer churn. The dataset is highly imbalanced (95% non-churn, 5% churn). Which metric should be prioritized for model evaluation?

A company uses AWS Lake Formation to manage data lakes for analytics. They want to ensure that only authorized users can access specific columns in a table containing sensitive data used for ML training. Which Lake Formation feature should they use?

A company uses an LLM to generate medical advice. They are concerned about hallucinations and want to implement safeguards. Which TWO techniques should they prioritize?

A developer is using Amazon Bedrock to build a chatbot that answers customer queries. The chatbot must only respond based on the provided company documentation. Which approach best meets this requirement?

A company is developing an AI system to screen job applications. They want to ensure the system does not discriminate against candidates based on gender. The dataset used contains historical hiring decisions that may reflect past biases. Which type of bias is MOST likely present in this scenario?

A company is building a chatbot that must provide accurate answers based on internal documents without retraining the model. Which approach should they use?

A research lab uses Amazon SageMaker to train a deep learning model for medical diagnosis. They need to ensure the model's decisions are interpretable to clinicians. Which SageMaker feature provides local and global feature importance?

A data engineer needs to ensure that all data uploaded to an S3 bucket for SageMaker training is automatically encrypted with a customer-managed key. Which S3 feature should they enable?

A developer is building an Amazon Bedrock Agent to automate multi‑step workflows like booking flights and hotels. The Agent needs to call an external flight reservation API. How should the developer expose this API to the Agent?

A company uses Amazon Bedrock to generate marketing copy. The summaries are too verbose. Which parameter should be decreased to directly limit the length of the output?

An AI system is used to screen job applications. The team finds that the model has a higher false positive rate for male applicants than female applicants. Which fairness metrics should they compute to quantify this disparity? (Choose two.)

A healthcare company is using Amazon Bedrock to summarize patient notes. The compliance team requires that no patient data is used to improve the underlying foundation model. Which configuration should the team choose?

A team is developing an AI system and wants to document key information such as intended use, performance benchmarks, and limitations. According to AWS best practices for responsible AI, what should they create?

An administrator reviews a CloudTrail log entry for a CreateModel API call. Which security concern should they investigate?

A company is developing an AI recruitment tool that screens candidates. They want to minimize bias and ensure compliance with emerging regulations like the EU AI Act. Which THREE measures should they implement? (Select THREE.)

A healthcare organization is using Amazon Bedrock to analyze medical images and generate radiology reports. They need to comply with HIPAA regulations and ensure patient data is not used for model training. Which configuration should they use?

A healthcare startup is using an LLM to summarize patient medical records. They are concerned about hallucinations where the model may invent symptoms or treatments. Which combination of techniques should they implement to reduce hallucinations while maintaining accuracy?

A company uses Amazon SageMaker to train a model on customer transaction data. The data is stored in an S3 bucket encrypted with SSE-KMS. The data scientists are using a SageMaker notebook instance to preprocess the data. The security team notices that the notebook instance can access the KMS key directly through the SageMaker console, even when the data scientists do not have explicit KMS permissions. What is the MOST likely reason for this behavior?

A company is using Amazon Comprehend to extract entities from customer support tickets. The compliance team requires that the text sent to Comprehend be encrypted in transit and that Comprehend does not store any data beyond the processing time. How should the company configure the API call?

A startup is building a recommendation engine for their e-commerce platform. They need a fully managed service that can generate personalized product recommendations based on user behavior. Which AWS service should they use?

A company is using Amazon Bedrock to generate code snippets. They want to ensure the generated code is secure. Which TWO practices should they implement?

Which TWO services can be used to preprocess data for machine learning in AWS? (Choose two.)

A financial services company is deploying a machine learning model to approve loan applications. To comply with regulatory requirements, they must ensure the model does not discriminate based on race. They have historical data that may contain bias. Which AWS service can help detect and measure bias in the dataset and model predictions?

A data scientist is using Amazon SageMaker Clarify to generate a bias report for a binary classification model. They want to understand which features most influence the model's predictions. Which feature of Clarify should they use?

A data scientist is fine-tuning a large language model on Amazon SageMaker for a text summarization task. The training loss decreases steadily but the validation loss starts increasing after a few epochs. What should the scientist do to address this issue?

A company wants to use Amazon Bedrock to build a multilingual customer support chatbot. The chatbot must answer questions in English, Spanish, and French. Which TWO actions should the company take to achieve this? (Select TWO.)

A company is using Amazon Rekognition to detect objects in images. They need to detect custom objects that are specific to their domain. What should they do?

A company wants to use a third-party foundation model in Bedrock and is concerned about the provider's data handling policies. Which action should they take to ensure their data is not used for model training by the provider?

A developer invokes an Amazon Bedrock model and receives the above response. What does the 'stopReason' field indicate?

A data scientist is using Amazon SageMaker Clarify to generate a model explainability report. They want to include both global and local feature importance. Which TWO techniques does SageMaker Clarify support for these purposes?

A developer attached this IAM policy to a role used by an application that invokes Claude v2 in us-east-1. The application receives an access denied error. What is the MOST likely cause?

A company is deploying an AI-powered document summarization system using Amazon Bedrock. They must ensure that the model only uses information from provided source documents and does not generate unsupported claims. Which Bedrock Guardrails feature should they enable?

A developer receives the above response from invoking a Bedrock model. Which field indicates that the model completed its response normally?

A company uses Amazon Bedrock to build a conversational AI. They want to enforce role-based access to the model. Which AWS service should they use?

A company needs to store large amounts of unstructured training data (images, videos) in a cost-effective manner while ensuring low-latency retrieval for training jobs running on Amazon SageMaker. Which storage solution should be used?

A media company uses a generative AI model to automatically create image captions for user-uploaded photos. During quality assurance, testers discover that the model sometimes generates captions that include stereotypes based on gender and race, even when the photos do not contain people. For example, a photo of a kitchen produces captions like 'woman cooking,' and a photo of a sports car generates 'man driving.' The company wants to launch the feature soon but recognizes the reputational risk. They have a limited budget and need to implement a solution that reduces harmful stereotypes without overly restricting the captions' creativity. The team has access to the model's training data, which is a large public dataset of image-caption pairs. Which approach should the team prioritize?

Which THREE considerations are important when implementing responsible AI for a production NLP system? (Choose three.)

A company wants to build a generative AI application that can automatically classify customer feedback into positive, neutral, or negative sentiments. Which foundation model capability is BEST suited for this task?

A company uses Amazon Bedrock to generate content. They need to guarantee that the model does not produce toxic or biased outputs and that any violations are logged for review. Which service should they integrate with Bedrock?

After deploying a model, a company notices that the distribution of the input features has shifted compared to the training data. Which feature of Amazon SageMaker Model Monitor can alert them to this change?

A company wants to use Amazon SageMaker to train a model on sensitive healthcare data. What is the MOST secure way to ensure that the training data is encrypted at rest and in transit, and that only authorized users can access the model artifacts?

A company fine-tunes a foundation model on SageMaker JumpStart for sentiment analysis. After deployment, the model shows bias toward positive sentiment. Which action should be taken to mitigate bias?

A company is deploying a generative AI model on Amazon Bedrock. The model is accessed by an application running on Amazon ECS Fargate. The security team requires that all data sent to and from the Bedrock model be encrypted in transit, and that the ECS task does not have internet access. The ECS tasks are launched in a private VPC subnet with a VPC endpoint for Bedrock configured. However, when the application attempts to invoke the Bedrock model, the call fails with a timeout error. The VPC endpoint policy is set to allow all actions from all principals. What is the most likely cause of the failure?

A company needs to secure data used for training machine learning models in Amazon SageMaker. Which TWO actions should be taken to protect data at rest and in transit? (Choose TWO.)

A company is using Amazon SageMaker to train a model. The training data is stored in an S3 bucket that is encrypted with an AWS KMS customer managed key (CMK). The training job fails with an error indicating that the SageMaker execution role does not have permission to decrypt the data. The administrator has verified that the execution role has the kms:Decrypt permission. What additional permission might be missing?

A company wants to build a system that automatically categorizes customer support tickets into predefined categories (e.g., billing, technical, account). The team has a large dataset of historical tickets with their category labels. Which type of machine learning problem is this?

Which parameter controls the randomness of generated text in a foundation model?

A financial institution uses a machine learning model to approve loan applications. To comply with regulatory requirements, they need to explain individual predictions. Which AWS service and feature combination should they use?

A company is evaluating different foundation models for a text summarization task using Amazon Bedrock. They want to use automated metrics to compare model outputs against reference summaries. Which TWO metrics are commonly used for summarization evaluation?

An organization uses Amazon Macie to discover sensitive data in S3. The compliance team needs to receive notifications when Macie finds PII. Which AWS service should they use to send notifications?

A data scientist is training a model using Amazon SageMaker and needs to ensure the training data is encrypted at rest and in transit. The data is stored in S3. Which combination of steps meets this requirement?

A startup uses Amazon Bedrock with a provisioned throughput to generate product images. They now have unpredictable traffic and want to reduce costs. What should they do?

A data scientist is fine-tuning a large language model (LLM) using Amazon SageMaker. The training job is taking a long time and the cost is higher than expected. Which configuration change would MOST effectively reduce training time and cost while maintaining model quality?

A developer is calling the Amazon Bedrock InvokeModel API to generate text with the AI21 Labs Jurassic-2 Mid model. The API call includes a maxTokens parameter, but the request fails with the error shown in the exhibit. What is the most likely cause of this error?

Refer to the exhibit. An IAM policy is attached to a role used by an Amazon SageMaker notebook instance. The notebook instance attempts to upload a model artifact to the S3 bucket 'my-bucket' without specifying server-side encryption. What will happen?

A company uses Amazon Bedrock to build a chatbot. The chatbot needs to answer questions based on internal company documents. Which AWS service should be integrated with Bedrock to enable Retrieval Augmented Generation (RAG) without managing infrastructure?

A healthcare company is using Amazon SageMaker to deploy a model that makes predictions on patient data. They need to ensure that the model's predictions are explainable to comply with regulations. Which approach should they take?

A data scientist is prototyping a text generation application using Amazon Bedrock. They want to quickly test different foundation models with various prompts and parameters without writing any code. Which AWS service or feature should they use?

A data scientist is using a pre-trained LLM for a text summarization task. They notice the model sometimes includes hallucinations (false information) in the summaries. Which THREE prompt engineering techniques can help reduce hallucinations? (Select THREE.)

A marketing agency wants to analyze customer feedback from social media posts to gauge sentiment. They have no labeled data and limited ML expertise. The team needs a managed service that provides pre-trained models for sentiment analysis without requiring them to train or manage infrastructure. They also need to process text in multiple languages. Which AWS service should they use?

A company uses Amazon Bedrock to generate content and wants to prevent the model from producing harmful or biased responses. Which AWS service should they configure to enforce content safety policies?

A developer is creating a generative AI application using Amazon Bedrock and needs to ensure that responses do not include toxic or harmful content. Which feature should be enabled?

A company is using Amazon SageMaker to train a model. They want to automatically stop training if the model performance stops improving on a validation dataset. Which SageMaker feature should they enable?

Refer to the exhibit. A data scientist is trying to run a SageMaker training job that uses training data from an S3 bucket encrypted with the specified KMS key. The training job fails with an access denied error. The IAM role shown is attached to the training job. What is the missing permission?

A company uses a text generation model to produce legal documents. They want to minimize the environmental impact of training and inference. Which THREE approaches should they consider?

A company wants to document their machine learning model's intended use, limitations, and ethical considerations. Which TWO practices should they adopt? (Choose two.)

An e-commerce company uses a recommendation system built with Amazon Personalize. They want to explain to customers why certain products are recommended. Which AWS service can provide model explanations?

Which THREE are SageMaker built-in algorithms suitable for regression tasks?

A data scientist wants to host a pre-trained model on Amazon SageMaker for real-time inference with minimal latency. Which approach should they use?

A data engineer is using Amazon SageMaker Data Wrangler to prepare tabular data for ML. Which THREE data transformations are natively supported? (Choose three.)

Which AWS services can be used to build, train, and deploy custom machine learning models? (Choose two.)

A media company uses Amazon Transcribe for automatic speech recognition. They discover the model has higher error rates for non-native English speakers. Which Responsible AI principle are they failing to uphold?

A company is using Amazon Bedrock to generate marketing copy. They want to evaluate the quality of the generated text. Which metric is MOST suitable for assessing the relevance and coherence of the content?

Which TWO practices help ensure responsible AI when deploying generative AI applications? (Select TWO.)

A company uses Amazon Bedrock to generate code. They want to ensure the code follows security best practices and does not contain vulnerabilities. Which approach is most effective?

An organization is implementing governance for machine learning models using SageMaker. They need to track model versions, monitor for drift after deployment, and automatically decommission models that have been deprecated for over 30 days. Which THREE services or features should they use?

A healthcare startup is deploying an AI system to assist in diagnosing skin conditions from images. They want to follow the NIST AI Risk Management Framework. Which THREE practices should they implement?

Which TWO actions are best practices when deploying foundation models on Amazon SageMaker for production? (Choose TWO.)

A company is developing an AI system for resume screening. They want to ensure fairness and reduce bias. Which THREE steps should they take in accordance with the NIST AI Risk Management Framework and AWS responsible AI principles?

Refer to the exhibit. A user invokes Claude v2 using the AWS CLI. The response is truncated. What is the most likely cause?

A company uses Amazon Bedrock to generate product descriptions. They notice that the output sometimes contains incorrect information. What should they do to improve accuracy?

Refer to the exhibit. A company sets up a knowledge base for a customer support chatbot using Amazon Bedrock. Users report that the chatbot misses relevant details from long documents. Which change to the data source configuration would most likely improve retrieval?

A company wants to build a generative AI application that can summarize customer support tickets. They need to ensure the model stays up-to-date with the latest product documentation without retraining. Which AWS service would best support this requirement?

A developer wants to experiment with a foundation model for code generation without writing any code. Which AWS service provides a playground for models like CodeWhisperer?

An AWS AI practitioner is designing a document processing pipeline using Amazon Textract and Amazon Comprehend. The pipeline must extract text from PDFs, detect entities, and classify documents into categories (e.g., invoice, contract, report). Which THREE steps should be included in the pipeline? (Choose three.)

A government agency is deploying an AI system to detect fraudulent benefit claims. The system uses a neural network trained on historical claims data, which includes a disproportionate number of false positives from a particular ethnic group due to historical over-policing. The agency must ensure the system does not perpetuate discrimination. They have a rigorous testing procedure but limited budget. The project lead wants to balance fairness with detection performance. Which combination of steps should they prioritize?

Which TWO techniques are commonly used to prevent overfitting in machine learning models? (Select TWO.)

A company builds an AI system that generates medical diagnoses. To ensure patient safety and allow oversight, the company wants a human to review all high-risk predictions before they are acted upon. Which AWS service should they use?

An ML engineer wants to store training data in a format optimized for linear data scanning and columnar access in SageMaker. Which format is most appropriate?

A company uses Amazon SageMaker to host a model for fraud detection. The model must be re-evaluated for bias on a monthly basis. Which SageMaker feature can be used to detect bias in a trained model?

A team is using Amazon SageMaker to deploy a real-time inference endpoint. The endpoint must be accessible only from a specific IP range and must automatically scale based on request volume. Which configuration meets these requirements?

A healthcare company wants to use generative AI to automatically generate patient summary reports from electronic health records (EHRs). The solution must be HIPAA compliant and data must not leave AWS. They plan to use Amazon Bedrock with a foundation model. The EHR data is stored in Amazon S3 and contains protected health information (PHI). Which approach best meets compliance requirements?

An ML team notices that the training accuracy is 99% but validation accuracy is only 72%. Which concept best describes this situation?

A company uses Amazon Bedrock Agents to automate order processing. The agent needs to call an internal database to check inventory. Which component should be used to integrate the database query?

A machine learning engineer notices that a SageMaker training job failed due to insufficient permissions to access a KMS-encrypted S3 bucket. The training job's IAM role has S3 access permissions. What should be done to resolve the issue?

A healthcare startup is deploying an AI model to assist with diagnosis. They want to comply with the EU AI Act, which classifies medical AI as high-risk. Which THREE requirements must they fulfill? (Choose three.)

Which of the following is a key advantage of using a pre-trained foundation model over training a model from scratch?

A company wants to use a third-party foundation model from Amazon Bedrock but is concerned about data privacy because the model provider might store prompts and responses. How should they address this concern?

A data scientist needs to use Amazon SageMaker to train a model and must ensure that the training data and the model artifacts are encrypted using customer-managed KMS keys. Which TWO resources can be encrypted with KMS keys in this scenario? (Select TWO.)

A financial services company is deploying a large language model (LLM) on Amazon Bedrock for customer-facing applications. The compliance team mandates that the model must not generate any content containing personally identifiable information (PII). Additionally, the company wants to ensure that the model only answers questions related to its product documentation and refuses off-topic queries. Which THREE Bedrock Guardrails configurations should be applied?

In a binary classification problem, the model predicts majority class for all inputs. What is this issue called?

An organization uses AWS Lake Formation to govern access to data used for machine learning in Amazon SageMaker. They want to ensure that a particular IAM role used by SageMaker can only query a subset of columns in a table containing sensitive customer data. Which Lake Formation permission should be granted to the role?

A company uses Amazon SageMaker Ground Truth to label a dataset for a binary classifier. To reduce labeling bias, which workforce configuration is most appropriate?

A company uses Amazon Comprehend to analyze customer sentiment. They discover the model performs poorly on text with slang from underrepresented groups. What is the most responsible action?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which metric is most appropriate for evaluating a classification model when false positives are costly?

A developer is building an application that uses Amazon Bedrock to answer questions based on a large internal knowledge base. The knowledge base contains PDFs, Word documents, and web pages. Which TWO AWS services are commonly used together to implement a Retrieval-Augmented Generation (RAG) architecture on AWS? (Select TWO.)

A company wants to use Amazon Bedrock to translate customer emails from English to Spanish. The emails contain occasional personal names and addresses. Which Guardrail configuration should be applied to protect customer privacy?

Refer to the exhibit. A data scientist ran a training job on Amazon SageMaker and it failed. Which action should the data scientist take FIRST to resolve the issue?

A data scientist is prototyping a text summarization application using Amazon Bedrock. They want to quickly test different prompts and models without writing code. Which AWS service or feature should they use?

A startup wants to generate high-quality images from text descriptions using Amazon Bedrock. They need to create realistic images of products for an e-commerce catalog. Which model provider should they choose?

A machine learning team is building a binary classifier using Amazon SageMaker. The dataset has 10,000 features and 1,000 samples. The model overfits severely. Which TWO approaches are MOST likely to reduce overfitting? (Choose two.)

A company wants to use AI to automatically transcribe customer service calls into text. Which AWS service is most suitable?

Refer to the exhibit. The training job is failing with an error 'CUDA out of memory'. Which hyperparameter change is MOST likely to resolve the issue?

A data science team is using Amazon SageMaker Studio. To meet compliance requirements, they need to ensure that all user activity in the environment is logged and that any unauthorized access attempts are detected. Which approach should they take?

A company is using Amazon Fraud Detector to detect fraudulent transactions. Which TWO actions can be taken to improve model accuracy? (Select TWO.)

A financial services company is building a predictive model using Amazon SageMaker. The model training data contains personally identifiable information (PII). The company must ensure that the data is encrypted at rest and in transit, and that access to the data is logged. Which combination of AWS services meets these requirements?

A company wants to build a customer support chatbot that answers questions based on a large internal knowledge base. Which AWS service is most suitable for implementing RAG to retrieve relevant documents?

A data scientist is using a foundation model to summarize long documents. Which TWO of the following steps are most likely to improve the quality of the summaries?

A team deployed a text generation model on Amazon Bedrock. They want to monitor for toxic content in model outputs. Which evaluation approach is MOST effective?

A company is developing an AI system that generates news articles. To comply with transparency regulations, they must clearly indicate when content is AI-generated. Which action should they take?

A company wants to automatically detect anomalies in their AWS CloudTrail logs to identify potential security threats. Which AWS service is specifically designed for this purpose?

Which TWO of the following are types of feature scaling?

A company is using Amazon Comprehend to analyze customer feedback. They need to ensure that the documents are encrypted at rest. What should they do?

A developer is using Amazon Bedrock to generate code snippets. The model often produces insecure code. Which prompt engineering technique is MOST effective to improve security?

A team trained a deep learning model that achieves 99% accuracy on training data but only 70% on validation data. What is the most likely issue?

Which THREE of the following are capabilities of Amazon SageMaker? (Select THREE.)

A company uses Amazon SageMaker to build and deploy models. They want to enforce compliance that all model endpoints are encrypted in transit and use least privilege access. Which THREE steps should they take? (Choose THREE.)

A company deploys a large language model to automatically generate product descriptions. They want to ensure customers are aware that the content is AI-generated, as part of transparency requirements. What should they implement?

During a security review, it is found that an Amazon SageMaker notebook instance has outbound internet access, which could lead to data exfiltration. The notebook must only access resources within the VPC. Which step should be taken to restrict internet access?

A developer is building an application using Amazon Bedrock and needs to ensure that the model's responses do not include any toxic or harmful language. Which Bedrock feature should they configure?

What is the main purpose of a system prompt in a large language model?

A developer is building a chatbot using Amazon Bedrock and Claude. They notice that the model sometimes generates harmful or biased responses. Which AWS service can they use to implement guardrails?

A company uses Amazon Bedrock to power a code generation assistant. They notice that the generated code sometimes contains security vulnerabilities. Which approach would BEST address this issue without sacrificing code quality?

A company is using Amazon SageMaker to train a large language model with hundreds of billions of parameters. The model does not fit into the memory of a single GPU. Which approach should they use to train the model efficiently?

A data scientist uses Amazon Bedrock. The model responses are too long. Which parameter should they adjust to limit the output length?

A SageMaker endpoint is configured with automatic scaling. The model's inference time is 50ms, and traffic increases gradually. What scaling metric should be used to add instances before latency increases?

A machine learning engineer is using Amazon SageMaker to deploy a real-time inference endpoint for a classification model. The model must provide low-latency predictions and handle variable traffic. Which THREE actions should the engineer take? (Select THREE.)

A company is deploying a real-time inference endpoint using Amazon SageMaker. The security team requires that all data sent to the endpoint be encrypted in transit and that the endpoint is only accessible from within the company's VPC. Which configuration should be used?

A company uses a foundation model for real-time translation in a chat application. The latency is high. Which optimization would reduce latency the most?

A company wants to use Amazon SageMaker Ground Truth to build a labeled dataset for a custom object detection model. Which TWO labeling strategies are available? (Choose two.)

A financial services company uses Amazon Bedrock to power a customer-facing chatbot that provides investment advice. The company must ensure that the chatbot's responses comply with regulatory standards, meaning that the model should not generate advice that is speculative or promises returns. The company has implemented Bedrock Guardrails with content filters. However, during testing, the chatbot still generates responses that violate the guidelines. A review of the guardrail configuration shows that the content filters are set to the lowest sensitivity. The company wants to enforce stricter filtering without completely blocking legitimate responses. What should the company do?

A developer is using Bedrock Studio to prototype a summarization application. They want to quickly test different foundation models and prompts without writing code. What should they use?

An AI team uses the IAM policy shown in the exhibit to control endpoint creation. Why does this policy support responsible AI?

A data scientist wants to quickly build a supervised learning model for binary classification on a tabular dataset with 10,000 rows and 200 features. The dataset has some missing values and requires minimal code. Which AWS service should the data scientist use?

A company wants to automatically detect anomalies in server metrics. Which algorithm is most appropriate?

Refer to the exhibit. A developer is optimizing latency for a generative AI model deployed on SageMaker. Based on the exhibit, which change would most likely reduce per-token latency?

Which vector store is a fully managed AWS service that can be used with Amazon Bedrock Knowledge Bases for semantic search?

A company is using Amazon Bedrock to generate creative marketing copy. They want to reduce the randomness of the output while maintaining diversity. Which TWO parameters should they adjust?

A company is using Amazon Rekognition to detect objects in images. They find that the service sometimes mislabels objects. What is the best way to improve accuracy for their specific use case?

Which THREE considerations are essential when deploying a generative AI application in a regulated industry such as healthcare?

A company is using Amazon Bedrock Knowledge Bases to power a legal document Q&A application. They need to ensure that the model only answers based on the retrieved documents and does not generate information not present in the documents. Which feature should they enable?

A company is building a resume screening model and discovers that the training data contains only resumes from one gender, leading to biased predictions. Which type of bias does this represent, and what is the most effective mitigation strategy?

A data science team is using Amazon SageMaker to train multiple models with different hyperparameters. They want to track metrics, compare runs, and reproduce the best result. Which SageMaker feature should they use?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A team has created a knowledge base in Amazon Bedrock for a Q&A application. After updating the source documents, they notice that the model still returns old information. What is the MOST likely cause?

A company is using Amazon SageMaker to manage the lifecycle of their machine learning models. They need to implement a governance framework that includes model versioning, monitoring for drift, and decommissioning of outdated models. Which THREE AWS services or features should they use together to meet these requirements? (Select THREE.)

A company is using Amazon Rekognition to detect objects in images stored in an S3 bucket. The company needs to ensure that the Rekognition service has permission to read images from the S3 bucket. Which TWO methods can achieve this? (Choose TWO.)

A company uses a generative AI model to create marketing copy. They want to ensure that customers know the content is AI-generated. Which practice directly addresses this transparency requirement?

A company is deploying a generative AI application using Amazon Bedrock and needs to optimize costs for a high-volume, latency-tolerant workload. Which TWO strategies should they implement? (Select TWO.)

A company wants to use Amazon Bedrock to generate personalized marketing emails. They have thousands of customer profiles with demographic data. To generate tailored content efficiently, the application must dynamically insert customer-specific information into prompts. Which prompt management technique is BEST suited for this?

A data scientist is using Amazon SageMaker Clarify to analyze a model and discovers that the model treats two different demographic groups differently when they should have similar outcomes. The data scientist wants to quantify this difference using a metric that compares the proportion of positive outcomes for each group. Which metric should be used?

Refer to the exhibit. A data scientist created this endpoint config for a foundation model in Amazon SageMaker. However, the endpoint fails to scale under load. What is the most likely reason?

A company is training a deep learning model on Amazon SageMaker using a large dataset stored in S3. Training jobs are frequently failing with 'OutOfMemoryError'. The training algorithm uses PyTorch. How should the data scientist solve this without reducing model accuracy?

A large e-commerce company uses a recommendation system to suggest products to customers. Recently, a data scientist noticed that the model's recommendations for high-value luxury items are predominantly shown to users in affluent zip codes, while users in less affluent areas rarely see these items, even if they have searched for them. The company is concerned about fairness and wants to ensure all customers have equal access to recommendations regardless of location. The current model uses collaborative filtering on historical purchase data. The team needs to modify the system without sacrificing overall recommendation accuracy. Which action best addresses the fairness concern while maintaining performance?

A company needs to generate high-quality images from text descriptions for a marketing campaign. They need to ensure the images are photorealistic and that the model can generate variations of a given image. Which type of model should they use?

During a SageMaker training job, the data scientist observes that the loss is not decreasing after the initial few epochs. The model is a deep neural network with ReLU activations. Which hyperparameter adjustment is most likely to help?

A company is using Amazon SageMaker JumpStart to deploy a pre-trained text generation model. After deployment, the model produces slow inference responses. Which action is most likely to improve inference latency?

A company is using Amazon Bedrock to generate text summaries of customer emails. The compliance team requires that any email containing a Social Security Number (SSN) must be blocked from being sent to the model for summarization. Which Bedrock Guardrail configuration should be used?

A company wants to extract text and data from scanned PDF invoices for automated processing. Which AWS service is MOST appropriate for this task?

A bank wants to use Amazon Augmented AI (A2I) to review high-value loan applications that require human judgment. Which workflow best implements human-in-the-loop review for these predictions?

A financial services company deploys a generative AI chatbot for customer support. They want to prevent the chatbot from generating harmful or misleading information. Which AWS service can help monitor and filter responses?

A data scientist is preparing data for a classification task. Which TWO techniques are commonly used for handling missing values? (Choose two.)

Refer to the exhibit. A SageMaker training job fails with an 'AccessDenied' error when trying to read files from the S3 bucket 'my-training-data'. The IAM role used by the training job has the policy shown. What is the most likely reason for the failure?

A legal firm uses Amazon Bedrock to generate contract summaries. They want to evaluate the quality of summaries against human-written reference summaries. The evaluation should capture both the overlap of n-grams and the semantic similarity. Which combination of automated metrics is MOST appropriate?

A financial services firm needs to ensure that all calls to Amazon Bedrock APIs are logged for audit purposes. Which AWS service should they enable to capture API calls?

A data science team uses Amazon SageMaker to train models. To comply with SOC 2, they must ensure that access to training data is logged, that the data is encrypted at rest, and that model training jobs are isolated from each other. Which THREE actions should they take? (Choose three.)

A company is deploying a generative AI application using Amazon Bedrock and needs to optimize costs. They expect variable traffic with occasional high spikes. Which TWO strategies would help reduce costs while maintaining performance?

A healthcare organization is deploying an AI system to assist in diagnosing diseases from medical images. They need to ensure the system is robust, safe, and subject to human oversight. Which TWO actions align with responsible AI guidelines? (Select TWO.)

A developer is using Amazon Bedrock to create a chatbot. They want to ensure the bot does not generate toxic or offensive content. Which feature should they enable?

A company is developing an AI system that transcribes medical consultations. To ensure privacy and security, they need to implement controls that protect patient health information (PHI). Which AWS service can help anonymize data before it is used for model training?

A data scientist is building a RAG application using Amazon Bedrock Knowledge Bases. They want to ensure that only the most semantically relevant documents are retrieved for each query. Which embedding model characteristic is MOST important for this requirement?

A company wants to track API calls made to Amazon SageMaker for audit purposes. Which AWS service should they enable?

A developer is trying to invoke the Claude v2 model in Amazon Bedrock from a Lambda function. The Lambda function's IAM role has the following policy attached: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "bedrock:InvokeModel", "Resource": "*" } ] } When the Lambda function runs, it receives the error shown in the exhibit. Which additional step is most likely needed to resolve this issue?

A company wants to build a generative AI application that generates personalized marketing emails based on customer data. They have a small dataset of past emails. Which AWS service should they use to fine-tune a foundation model with their data?

A healthcare startup is using Amazon SageMaker to train a model on patient data. They need to ensure that the training data does not contain any personally identifiable information (PII) before being used. Which AWS service can automatically detect and report PII in the data stored in S3?

A startup wants to generate product descriptions from a few keywords using a foundation model. They need a fully managed serverless solution that requires no infrastructure setup. Which AWS service should they use?

A company wants to reduce the cost of running a large number of inference requests for a text classification task. The responses can tolerate a slight delay. Which cost optimization strategy should they implement?

Refer to the exhibit. A developer deploys this CloudFormation stack but the agent fails to query the knowledge base. What is a likely cause?

A company using Amazon Bedrock needs to redact personally identifiable information (PII) from user inputs before sending them to the foundation model. Which Bedrock Guardrails component should be configured?

A company is using Amazon Bedrock to build a text-to-SQL application. They want to ensure that the generated SQL queries are valid and safe. Which approach is BEST?

An organization is using Amazon Bedrock to power a customer service chatbot. They notice that the chatbot occasionally generates hallucinated information about product specifications. Which strategy should be implemented to reduce hallucinations?

A company uses Amazon Bedrock to deploy a foundation model for a real-time chat application. Users report that responses are slow. Which optimization is MOST likely to reduce latency without degrading quality?

A developer needs to reduce costs for a Bedrock application that processes high volumes of similar queries. The queries are repetitive and the model is invoked many times with the same prompt. Which cost optimization technique is MOST suitable?

A company is using Amazon Bedrock to build a generative AI application. The company wants to prevent the model from generating toxic or harmful content while still allowing creative responses. Which feature should the company enable?

A startup is deploying a foundation model on Amazon SageMaker for real-time inference. They notice high latency (over 2 seconds per request). Which action is most likely to reduce latency?

A company is using Amazon Bedrock Agents to build a travel booking assistant that can search for flights, book hotels, and answer questions about travel policies. Which TWO components are required to enable the agent to call external services? (Select TWO.)

What does the temperature parameter control in a text generation model?

Which TWO of the following are valid methods to reduce the risk of foundation models generating harmful or biased content?

An e-commerce company uses Amazon Bedrock to generate product descriptions from keywords. Some descriptions contain inaccurate details about product specifications. Which approach should the company take to reduce factual errors?

A company wants to classify customer emails into categories (e.g., complaint, inquiry, feedback) using a foundation model. Which approach is MOST efficient?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Refer to the exhibit. A security analyst is reviewing CloudTrail logs and notices a training job creation from an IP address (203.0.113.5) that is not associated with the company's network. What is the most likely cause?

A developer wants to test different foundation models quickly without setting up infrastructure. Which AWS service allows interactive prompting and comparison of multiple models?

A data scientist is using Amazon SageMaker to train a model. The training job is taking longer than expected. Which change would most likely reduce training time?

A company needs to audit all API calls made to Amazon Bedrock, including model invocations and guardrail evaluations. Which AWS service should they enable to capture these API calls for compliance?

A company is using Amazon Bedrock to generate images from text prompts. They need to ensure the generated images do not contain offensive content. Which feature should be enabled?

Which TWO factors are most important when selecting a foundation model in Amazon Bedrock for a text summarization task with strict latency requirements?

Which TWO actions can help reduce the likelihood of hallucinations in a generative AI model used for question answering?

A company uses an LLM to summarize medical research papers. They are concerned about hallucinations. Which combination of techniques would most effectively reduce hallucinations in this context?

A retail company uses a recommendation system that occasionally suggests inappropriate products to minors. Which responsible AI practice should be applied?

A company uses Amazon SageMaker to train a model. The training job fails with 'InsufficientInstanceCapacity' error. What is the most likely cause?

A company is training a deep learning model for image classification. Which THREE practices help reduce overfitting? (Choose three.)

An organization uses SageMaker JumpStart to deploy a foundation model for real-time inference. They observe high latency. What is the most effective way to reduce latency?

A company wants to prevent an Amazon Bedrock chatbot from discussing specific prohibited topics like competitor pricing. Which Bedrock feature should they configure?

Which of the following is a primary benefit of using Bedrock Agents for building generative AI applications?

A data scientist is evaluating a logistic regression model for a binary classification task. The model's AUC-ROC score is 0.95 on the training set and 0.51 on the test set. What is the MOST likely issue?

A financial services firm needs an LLM-powered application that analyzes customer transaction data and generates compliance reports. The data contains personally identifiable information (PII). The firm must ensure that no training data includes PII, and that the LLM never outputs PII. Which combination of AWS services and practices should they use?

Which THREE are benefits of using Amazon Bedrock over self-managing foundation models on EC2? (Choose THREE.)

An e-commerce company uses an LLM to generate product descriptions. They observe that occasionally the model outputs factually incorrect information about products. What is the term for this phenomenon?

Which AWS service provides human review workflows to handle low-confidence predictions or high-risk decisions in an AI system?

A financial services company uses Bedrock Agents to automate a multi-step loan approval process. The agent needs to call an external credit scoring API and a compliance database, then combine results. The agent currently fails when the API returns a 503 error. How should the practitioner address this?

A financial services company is deploying a foundation model to analyze customer sentiment from call transcripts. The model outputs must be consistent and deterministic for auditing purposes. Which parameter configuration should the company use?

An AI practitioner is fine-tuning an Amazon Titan Text model on a dataset of customer support conversations to improve response accuracy. After training, the model's perplexity on the validation set is low, but during inference, the model frequently generates off-topic or nonsensical responses to real customer queries. What is the most likely cause?

A developer needs to preprocess a dataset consisting of customer reviews for sentiment analysis. Which text preprocessing technique is most likely to improve model accuracy?

What is the primary role of the self-attention mechanism in the Transformer architecture?

A company is using Amazon SageMaker to train machine learning models. The security team wants to ensure that the training data is encrypted at rest and that the SageMaker notebook instances cannot access the internet. Which TWO actions should the company take? (Choose TWO.)

A financial services firm uses Amazon Bedrock to generate investment summaries. They need to prevent the model from generating content containing personally identifiable information (PII) such as social security numbers. Which feature should they configure in Bedrock Guardrails?

Refer to the exhibit. A team is creating an IAM policy for a SageMaker notebook user. The user needs to access training data in an S3 bucket and create models. Which responsible AI concern is most relevant to this policy?

An organization is required to provide transparency about AI-generated content. Which of the following is the best practice to comply with transparency requirements?

A company uses Amazon Bedrock Agents to automate a multi-step customer support workflow. The agent needs to query a customer database and update a ticket system. Which TWO components are required to enable the agent to interact with these external systems?

A company wants to predict customer churn. They have historical data with features like usage minutes, support tickets, contract length. The target is binary: churn/not churn. Which ML algorithm is best suited?

A financial services company uses Amazon Rekognition to verify customer identities. To ensure responsible AI practices, which measure should the company prioritize?

A company is building a content generation application using Amazon Bedrock. They need to ensure that the model does not generate offensive content and also avoids discussing certain prohibited topics. Which TWO Bedrock features should be combined to achieve this?

Refer to the exhibit. A developer sees this error when calling Amazon Bedrock for inference. What is the MOST likely cause and recommended solution?

Which TWO of the following are key components of a responsible AI governance framework?

An AI practitioner is evaluating a text generation model and notices that the model sometimes produces plausible-sounding but factually incorrect statements. What is this phenomenon called?

A data scientist is using Amazon Bedrock to build a question-answering system over a large corpus of technical manuals. They want to ensure that the model's answers are grounded in the retrieved documents and that the model does not hallucinate. Which feature should they enable?

A developer is using Amazon Bedrock's Claude model to summarize long documents. The developer notices that the summaries sometimes miss key points. Which parameter adjustment is most likely to improve summary completeness?

A research team is using Amazon Bedrock to analyze scientific papers. They want the model to generate answers based only on papers published after 2023. Which approach should they use?

A financial services firm wants to deploy a generative AI application that answers customer questions about account balances and recent transactions. The firm has strict latency requirements (responses under 2 seconds) and wants to minimize costs. Which strategy for model selection and deployment is MOST appropriate?

A company is using an LLM to generate customer support responses. They want to reduce hallucinations and improve the accuracy of the responses. Which TWO approaches are most effective? (Select TWO.)

A company is building a RAG application that indexes thousands of PDF documents. They notice that some documents are very long (hundreds of pages) and the vector search often returns irrelevant chunks. Which configuration change would MOST improve retrieval relevance?

A machine learning team wants to detect bias in a deployed model's predictions on new data. They use Amazon SageMaker. Which service should they use to generate bias reports after deployment?

A security engineer is configuring logging for Amazon Bedrock model invocations. They need to capture both the input and output of all API calls for compliance audits. Which set of steps should they take?

A company wants to enforce strict data residency for training data used in SageMaker. The data must never leave a specific AWS Region. Which THREE actions should they take? (Choose 3)

An IAM policy allows creation of SageMaker training jobs only if they use a specific VPC security group. A user tries to create a training job without specifying that security group. What will happen?

A data science team is fine-tuning a Llama 2 7B model on Amazon SageMaker for a text classification task. After the first training run, they notice the loss is not decreasing and the model is overfitting to the small training set. What should the team change to mitigate overfitting?

A company has built a RAG application using Amazon Bedrock Knowledge Bases. Users report that answers are sometimes based on irrelevant or incorrect document chunks. The team has verified that the embedding model is appropriate and the documents are correctly indexed. What is the MOST likely cause of the poor retrieval quality?

Which TWO AWS services can be used to monitor and detect security anomalies in Amazon SageMaker model inference data? (Choose TWO.)

A company uses Amazon Bedrock to generate marketing copy. They want to measure the quality of generated text compared to reference text. Which metric is most appropriate?

A company is developing a chatbot using Amazon Bedrock and wants to ensure the model's responses do not include toxic or biased language. The company has a labeled dataset of undesirable responses. Which approach should be used to fine-tune the foundation model to reduce harmful outputs?

A startup is building a code generation assistant using a large language model. They want to evaluate the quality of generated code compared to reference implementations. Which automated metric is MOST suitable for this task?

A data scientist is using Amazon Bedrock to generate product descriptions. They notice the output is often repetitive and lacks creativity. Which combination of parameter adjustments is MOST likely to produce more diverse and less repetitive output?

A company wants to forecast product demand across thousands of SKUs with different demand patterns. They have 3 years of historical sales data, plus external factors like holidays and promotions. Which combination of AWS services and approach would deliver the most accurate forecasts with minimal manual effort?

A bank uses an AI system to detect fraudulent transactions. The model has high precision but low recall for small transactions, potentially missing fraud. Which approach aligns with responsible AI?

A company is evaluating the performance of their question-answering model using Amazon Bedrock's model evaluation feature. They want to assess both the factual accuracy and the fluency of the generated answers. Which THREE metrics should they choose? (Select THREE.)

A company wants to use a foundation model to automatically summarize lengthy documents. Which capability of foundation models is being utilized?

A company uses Amazon Bedrock to generate code snippets for internal tools. They notice that the generated code often contains security vulnerabilities such as SQL injection and cross-site scripting. The security team has compiled a comprehensive list of secure coding guidelines and examples of vulnerable patterns. The development team wants to reduce vulnerabilities without significantly slowing down the code generation process. They have tried adding the guidelines to the system prompt, but the model still produces insecure code occasionally. The team is considering additional measures. Which action should they take to most effectively eliminate security vulnerabilities in the generated code?

A company uses Amazon Bedrock to generate marketing copy. They want to evaluate the quality of generated text against human-written reference texts using automated metrics. Which metric measures the overlap of n-grams between generated and reference text?

A startup needs to predict customer churn based on historical data containing labels (churned or not). Which type of machine learning should they use?

A deployed model on an Amazon SageMaker endpoint is experiencing high inference latency (average 500ms) during peak hours. The model is a deep neural network with 10 million parameters. The endpoint uses a single ml.c5.xlarge instance. The company wants to reduce latency to under 200ms without retraining or changing the model architecture. Which action should they take?

A company wants to log all model invocation requests in Amazon Bedrock for audit and troubleshooting. Which TWO destinations can they configure for invocation logging? (Choose 2)

An e-commerce company uses Amazon Personalize to provide product recommendations. The business team observes that the recommendations are dominated by popular items and rarely suggest niche products, even for users with long purchase histories. Which Personalize recipe or configuration change would BEST address this issue?

A company is deploying a real-time chatbot using Amazon Bedrock and expects high traffic during business hours. They want to minimise inference costs while maintaining low latency. Which combination of strategies would be MOST effective?

A company wants to monitor for malicious activity in their machine learning pipelines, such as unauthorized access to training data or model artifacts. Which AWS service can provide automated threat detection and continuous monitoring?

An e-commerce company uses a foundation model to generate personalized email subject lines. The marketing team notices that the subject lines sometimes contain product recommendations that are out of stock. Which action would best reduce the generation of out-of-stock recommendations without retraining the model?

A social media company needs to automatically detect and flag toxic comments in multiple languages. They have a large stream of user comments and require real-time moderation. Which AWS service is best suited for this task?

A financial services company uses a machine learning model to automatically reject credit card transactions suspected of fraud. The model was trained on transaction data from the past two years. Over the last three months, the model's false positive rate has increased significantly, causing legitimate transactions to be declined and leading to customer complaints. The company needs to restore the model's accuracy quickly. Initial analysis shows that the distribution of transaction amounts and locations has shifted compared to the training period. The data science team is under pressure to deploy an update within a week. Which approach should they take to most effectively address the issue while adhering to responsible AI guidelines?

A data scientist observes that a gradient boosting model's performance on the validation set is significantly worse than on the training set. Which adjustment is MOST likely to reduce this gap?

A data scientist wants to use a third-party foundation model from Amazon Bedrock for a generative AI application. The compliance officer needs to understand how the third-party model provider handles data privacy. Where can the data scientist find this information?

A data scientist is fine-tuning a foundation model on Amazon Bedrock for a custom summarization task. Which THREE practices should they follow to optimize the fine-tuning process?

A company is implementing a Retrieval-Augmented Generation (RAG) pipeline with Amazon Bedrock Knowledge Bases. They need to store vector embeddings for their documents. Which vector store options are natively supported by Bedrock Knowledge Bases?

A healthcare company is deploying a machine learning model on Amazon SageMaker to analyze patient records. The model requires access to a DynamoDB table containing patient data. Which combination of AWS services and features should the company use to restrict access to only the necessary resources?

A media company uses Amazon Bedrock to generate image captions. They notice that the output quality degrades when the input image contains text in non-Latin scripts. Which model type is MOST likely being used, and what is the likely cause?

A healthcare company is using Amazon SageMaker to train and deploy a model that predicts patient readmission risk. The model uses sensitive protected health information (PHI). The company must ensure that data is encrypted at rest and in transit, and that access to the model endpoint is restricted to authorized applications only. The security team has configured AWS KMS customer managed keys for encryption, and IAM roles for SageMaker execution. However, during a security audit, it was discovered that the model endpoint is accessible from the internet and that the data used for training was stored in an S3 bucket with default encryption enabled. The compliance team requires that all PHI data be encrypted with a key that is rotated annually, and that no public access is allowed to the endpoint or training data. Which combination of actions should the ML engineer take to remediate these issues?

A developer wants to generate product description images using Amazon Bedrock. They need to ensure the generated images match a specific brand style. Which feature should they primarily use?

What is the primary purpose of chunking in a Retrieval-Augmented Generation (RAG) pipeline?

An organization wants to use Amazon Rekognition to analyze images of people for a security application. They must comply with GDPR. What is the best practice?

A machine learning team is training a model using Amazon SageMaker with data stored in an S3 bucket. The security policy requires that all data be encrypted at rest and in transit, and that the training job cannot access the internet. Which combination of settings should the team use?

A developer invoked an Amazon Bedrock model and received the following error: 'ValidationException: 1 validation error detected: Value 'claude-instant-v1' at 'modelId' failed to satisfy constraint: Member must satisfy enum value set: [ai21.j2-mid-v1, amazon.titan-text-lite-v1, anthropic.claude-v2, ...]'. What is the likely cause?

An organization wants to document their model's intended use, limitations, performance metrics, and ethical considerations. Which tool or practice is designed specifically for this purpose?

A team is deploying a generative AI model for medical report generation. They must ensure patient data privacy and comply with HIPAA. Which AWS service feature is essential for de-identifying protected health information (PHI) before sending data to a foundation model?

A company uses Amazon Rekognition for facial analysis. They want to ensure the model doesn't exhibit bias based on skin tone. What should they do?

A developer encounters the error shown above when using Amazon Bedrock. What is the most likely cause?

A financial services firm is deploying a loan approval model and must comply with the EU AI Act, which classifies credit scoring as a high-risk AI system. Which combination of actions is required for such high-risk systems under the regulation?

A company is deploying a generative AI application for customer support. They need to ensure that the model does not generate responses containing personally identifiable information (PII) even if it appears in the retrieved context. Which Bedrock feature should they configure?

A company is deploying a machine learning model for real-time fraud detection. The model must have latency under 100ms. Which infrastructure choice is most appropriate?

A team is using Amazon Bedrock to generate images from text prompts. The generated images often contain artifacts and do not match the prompt description. Which combination of steps should the team take to improve image quality?

A data scientist is using Amazon SageMaker to train a large language model from scratch. Which AWS service is most suitable for managing the training infrastructure, including automatic scaling and spot instance recovery?

Refer to the exhibit. A SageMaker real-time endpoint is experiencing increasing latency and memory errors after running for a few hours. What is the most likely cause and recommended fix?

An e-commerce company is using a foundation model to generate product descriptions. They want to reduce costs by caching frequently requested descriptions. Which AWS service should they use to implement a cache?

A company uses Amazon Bedrock to generate marketing content. They want to reduce costs while maintaining response quality. Which action is most effective?

A financial institution is deploying a fraud detection model using Amazon SageMaker. The model must be able to handle sudden spikes in inference requests during promotional events while keeping costs low. The team wants to use a serverless architecture to avoid provisioning idle capacity and to scale automatically from zero. However, the inference latency requirement is under 5 seconds for each request. Which SageMaker inference option should they choose?

A developer is building a multi-step reasoning agent using Amazon Bedrock Agents. The agent needs to first check inventory levels via a database query, then call a shipping API to calculate delivery dates, and finally compose a response. How should the developer define the tool integrations?

Which THREE of the following are factors to consider when selecting a foundation model for a text generation task?

A company uses Amazon Bedrock to generate summarizations of lengthy reports. Users report that the summaries are too verbose and include excessive detail. Which prompt engineering technique should the team apply to address this issue?

A developer is building a RAG application on Amazon Bedrock. They notice that the model sometimes generates answers that are not supported by the retrieved documents. To reduce this, they want to enforce that the model only uses the provided context. Which Bedrock feature should they use?

A company uses Amazon Bedrock and needs to log all model invocations for audit purposes. The logs must be stored in a central S3 bucket and also sent to CloudWatch Logs for real-time monitoring. Which configuration should they use?

A team is evaluating a classification model. The confusion matrix shows: TP=80, FN=20, FP=10, TN=90. What is the precision?

A company has deployed a machine learning model using Amazon SageMaker and wants to monitor the model for bias over time. Which SageMaker feature should they use to detect bias in the model's predictions after deployment?

A company develops a chatbot using Amazon Lex. To ensure transparency, what should the chatbot do when it cannot answer a question?

A data scientist wants to restrict which IAM roles can invoke a specific Amazon Bedrock base model. Which AWS feature should they use?

A developer is using Amazon Bedrock to generate responses from a foundation model and wants to receive the output as a stream to improve user experience. Which TWO statements about streaming responses are correct? (Select TWO.)

Which AWS service can be used to create human review workflows for high-risk AI predictions, ensuring a human-in-the-loop?

A company uses Amazon Bedrock to build a generative AI application. They need to secure the application by restricting access to the model and preventing sensitive data from being stored in prompts. Which TWO actions should they take? (Choose two.)

Which TWO AWS services can be used together to build a chatbot that leverages a foundation model for natural language understanding?

A company is using a machine learning model to predict employee turnover. The model's predictions are used to identify at-risk employees for retention efforts. The company wants to ensure that the model does not inadvertently discriminate against employees based on age. Which metric should be used to measure fairness across age groups?

A team is training a deep learning model using Horovod distributed training on SageMaker. They observe that the loss stops decreasing after a few epochs. Which technique should they implement to reduce overfitting?

A company is building a generative AI application using Amazon Bedrock. They need to implement a RAG pipeline that ingests PDF documents, processes them, and stores embeddings for retrieval. Which THREE steps are essential in this pipeline?

A company wants to build a system that automatically routes support tickets to the appropriate department based on the text description. They have labeled historical data. Which THREE AWS services could be used to implement this solution? (Select THREE.)

A company uses Amazon Bedrock Agents to build an agent that interacts with users through a chat interface. The agent is configured with a knowledge base containing product documentation. Sometimes the agent fails to answer simple questions like 'What is your return policy?' and instead says it cannot find the answer. The knowledge base does contain the return policy. What is the most likely reason?

A team is fine-tuning a foundation model using SageMaker. They want to minimize training time while keeping the model's original knowledge. Which technique is BEST suited?

A team is deploying a sentiment analysis application using Amazon Bedrock. They need to ensure the model returns only 'positive', 'negative', or 'neutral'. Which prompt engineering technique is BEST suited for this requirement?

A company is implementing an AI governance framework for their machine learning models deployed on Amazon SageMaker. Which THREE actions should they include to manage the model lifecycle effectively? (Select THREE.)

A developer is evaluating generative AI models for a code generation task. Which THREE metrics are commonly used for automated evaluation of generated code? (Choose THREE.)

A startup with limited ML expertise wants to quickly prototype a binary classification model using a small customer dataset. They need a managed environment to run Jupyter notebooks and access pre-built algorithms. Which AWS service should they choose?

A company deploys a machine learning model for resume screening. They want to measure whether the model selects candidates proportionally across different demographic groups. Which fairness metric is most appropriate?

A media company runs batch inference jobs to generate captions for thousands of images weekly using a foundation model on Amazon Bedrock. They want to minimize costs while maintaining predictable throughput. Which pricing option should they choose?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A data scientist is building a binary classification model for fraud detection. The dataset is highly imbalanced (99% legitimate, 1% fraud). Which metric is most appropriate to evaluate model performance?

A company is deploying an Amazon Lex chatbot that processes customer credit card information. The company must ensure that the chatbot does not log sensitive data and that the data is encrypted in transit. Which THREE actions should the company take? (Choose THREE.)

A data scientist is fine-tuning a foundation model on a custom dataset using Amazon SageMaker. After training, the model shows high accuracy on training data but poor on validation. Which action should be taken?

A company needs to ensure that model inference endpoints in SageMaker are only accessible from a private subnet in their VPC, and no traffic goes over the public internet. Which network configuration should they use?

Which AWS service is used as a vector store in Amazon Bedrock Knowledge Bases for storing and retrieving embeddings?

A company uses Amazon SageMaker to train sensitive ML models. Which AWS service should they use to encrypt the training data and model artifacts at rest?

A machine learning team is building a credit risk model and discovers that the training data has a significant imbalance in loan approval rates between two demographic groups. They decide to reweight the training samples using a preprocessing technique. Which SageMaker Clarify feature can help compute the appropriate sample weights to achieve demographic parity?

A developer is using the Amazon Bedrock Converse API to build a multi-turn conversational AI. They need to send a user message along with system instructions and previous conversation history. How should they structure the API request to include both system prompt and message history?

A company uses Amazon Rekognition to analyze images for a user-generated content platform. To comply with data residency requirements, they must ensure that images are not processed outside a specific AWS region. What should the company do?

A healthcare company is deploying a model to predict patient readmission risk using Amazon SageMaker. The model processes protected health information (PHI). The company must adhere to HIPAA regulations, which require that all PHI is encrypted at rest and in transit, and that access to the data is logged and audited. The data is stored in an S3 bucket encrypted with SSE-S3. The SageMaker training job uses a custom Docker container that reads data from the S3 bucket and writes model artifacts back to another S3 bucket. The security team notices that the model artifacts in the output bucket are not encrypted. Also, the training logs in CloudWatch Logs contain PHI because the training script logs patient features. The company must fix these issues without delaying the deployment. What should the company do?

A financial services company is deploying a generative AI chatbot to assist customers with account inquiries. The company wants to ensure the chatbot does not generate biased or harmful responses. Which combination of AWS services and practices should the company implement to monitor and mitigate these risks?

Which TWO of the following are best practices for preparing training data for a machine learning model?

A data science team wants to document and share their model's intended use, performance, and limitations with stakeholders. They also need to track the model's version and deployment history. Which TWO AWS services or features should they use?

Refer to the exhibit. A developer runs this command but gets an error: 'An error occurred (AccessDeniedException) when calling the ListFoundationModels operation'. What is the most likely cause?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company uses Amazon Bedrock Guardrails to filter harmful content. They want to ensure that the model does not generate responses containing specific keywords related to their internal project names. Which Guardrails component should they configure?

A company wants to use AWS services to process natural language text. Which TWO AWS services provide natural language processing (NLP) capabilities? (Select TWO.)

Which THREE considerations are essential for ensuring responsible AI in a model that predicts employee performance? (Choose 3)

A financial institution is using Amazon Bedrock for a customer-facing application. They must ensure compliance with data residency requirements: model inputs and outputs must not leave a specific AWS Region. Which THREE steps should they take? (Choose THREE)

A research team is using Amazon SageMaker to fine-tune a large language model. They want to optimize training cost and time without sacrificing model quality. Which THREE strategies should they implement? (Choose 3)

A financial services company is deploying a fraud detection model using Amazon SageMaker. They need to ensure that inference requests are encrypted in transit and that the model endpoint is only accessible from within a VPC. What is the MOST secure way to achieve this?

A company uses Amazon Macie to discover sensitive data in an S3 bucket containing training datasets. The bucket policy currently prohibits access from external accounts. Which TWO steps are necessary to allow a cross-account SageMaker training job to access this bucket while maintaining security?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A developer is building an agent using Amazon Bedrock Agents to handle customer support inquiries. The agent needs to look up order status from a database and escalate complex issues to a human. Which THREE components are essential for this agent?

A healthcare startup uses Amazon SageMaker to train a model predicting patient readmission. They need to ensure the model's predictions do not discriminate based on protected attributes like age or race. Which SageMaker feature allows them to monitor and mitigate bias during training?

A company is using Amazon Bedrock to generate content for a marketing application. The company wants to ensure that the model does not generate content that violates the company's brand guidelines, which prohibit certain keywords and tones. Which TWO features should the company use to enforce these guidelines? (Choose two.)

A healthcare organization uses an ML model to predict patient readmission risk. The model performs well overall but has significantly higher false negative rates for elderly patients. The team needs to mitigate this bias. Which step should they take FIRST?

A machine learning team uses Amazon SageMaker to train and deploy models. They need to ensure that only approved base models from the AWS Marketplace are used. Which feature should they use to enforce this policy?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A company is deploying an AI-based customer service chatbot using Amazon Lex and AWS Lambda. The company must ensure compliance with GDPR by allowing users to request deletion of their personal data collected during conversations. Which TWO actions should the company take? (Choose two.)

Refer to the exhibit. A company has the S3 bucket policy shown above. The company uses Amazon Rekognition to analyze images in the 'my-images' bucket. An IAM role used by a Lambda function calls Rekognition. Why might Rekognition be unable to read images from the bucket?

A developer is building a chatbot that must refuse to answer questions about internal financial data. They also need to filter out any offensive language from user inputs. Which TWO Bedrock features should they use? (Choose TWO.)

A company wants to build a multi-language customer support chatbot using Amazon Bedrock. The chatbot should support English, Spanish, and French. The team needs to translate user queries into English before processing and then translate responses back. Which TWO approaches could achieve this? (Choose TWO)

A developer is using Bedrock Agents to create a travel planning assistant. The agent needs to call a hotel booking API and a flight API. What is the correct way to define these external API calls in Bedrock Agents?

A company is building a chatbot using Amazon Bedrock to answer customer questions about their product catalog. The chatbot should only use information from the company's internal knowledge base and should not generate answers based on the model's pre-training data. Which feature should be enabled?

An AI practitioner is training a resume screening model and discovers that the model has a significantly lower recall for female candidates compared to male candidates. Which type of bias is MOST likely present?

A company wants to use AWS Lake Formation to govern access to data used for AI training. They need to ensure that only approved columns of sensitive tables are visible to data scientists. Which THREE steps should they implement? (Choose THREE)

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

An enterprise deploys a foundation model on Amazon Bedrock with a knowledge base. Users report that the model is returning outdated information. What is the most likely cause?

Which THREE statements about Amazon SageMaker Ground Truth are correct? (Choose three.)

A developer is using the Amazon Bedrock InvokeModel API with a model that has a context window of 8,000 tokens. The developer sends a prompt that is 7,500 tokens long and expects a response of about 1,000 tokens. The API call fails with an error indicating the input exceeds the model's context window. Why did this happen?

A company is using Amazon Bedrock Knowledge Bases with a RAG pipeline. They want to improve the relevance of retrieved chunks for user queries. Which TWO configuration changes are likely to help?