Review Mode Set 1 – AWS Certified AI Practitioner

A data science team is working on a computer vision project that involves training a deep learning model using a large dataset of labeled images.

Which of the following best practices should the team follow to ensure the security and integrity of its training data? (Select TWO.)

A machine learning engineer is evaluating the performance of a generative model system used for customer support. The engineer needs to identify key performance metrics and optimize the model for better response accuracy and efficiency.

Which business metric would best evaluate the model’s performance?

A retail company wants to improve its customer engagement by providing personalized recommendations to online shoppers. They decide to leverage generative AI to achieve this goal.

Which characteristics of a Generative AI system are relevant for creating personalized product recommendations? (Select THREE.)

A financial organization is planning to integrate generative artificial intelligence (generative AI) services into its workflow to improve customer support with natural language processing capabilities. The company is keen on ensuring that its AI models are transparent, fair, and accountable. They are looking for resources to understand the ethical implications and responsible use of AI services.

Which AWS service would be appropriate for this task?

An organization plans to implement an artificial intelligence (AI) system to assess and recommend individuals for eligibility in various public health initiatives and social welfare programs. The system analyzes data from multiple sources, including census data, employment records, and financial information. The organization needs to streamline the application process and ensure that eligible individuals receive the support they need.

Which core dimension of responsible AI should the organization prioritize to ensure that the machine learning model aligns with ethical principles and provides clarity on how decisions are made?

An organization plans to implement an artificial intelligence (AI) system to assess and recommend individuals for eligibility in various public health initiatives and social welfare programs. The system analyzes data from multiple sources, including census data, employment records, and financial information. The organization needs to streamline the application process and ensure that eligible individuals receive the support they need.

Concerns about data quality and model trustworthiness have been raised. To address these, which TWO core dimensions of responsible AI should the organization focus on? (Select TWO)

A financial expert is building a model to predict the future value of a portfolio based on historical performance, asset allocation, and market trends. The prediction model will help in making investment decisions and optimizing the portfolio allocation strategy.

Which machine-learning technique should be considered to meet this objective?

A healthcare insurance company manually extracts sensitive information from claims forms and accompanying attachments. This manual process has led to significant delays for customers seeking healthcare benefits. To improve customer service and reduce the manual labor involved, the company wants to automate the extraction process to expedite the handling and processing of claims.

Which AWS service will help meet the company’s objectives?

A company is planning to build a chatbot to analyze customer reviews using large language models (LLMs). They are evaluating various LLMs to find the one that best predicts whether a review is positive, negative, or neutral while also ensuring it removes sensitive information before processing. This step is crucial for preventing unintended consequences and complying with privacy regulations

Which of the following options will meet the requirements? (Select TWO.)

A technology company is exploring the use of generative AI models, such as large language models (LLMs), for various applications. However, the company is committed to ensuring that these models are deployed in accordance with the principles of responsible AI.

Which of the following are significant challenges of generative AI that need to be considered by the company? (Select THREE)

An AI specialist is working with a deep-learning model in Amazon SageMaker. The model is too large to fit into the memory of a single GPU, and the training dataset is also quite extensive. The specialist must choose a SageMaker built-in option to optimize the training process and manage the large model and dataset.

Which SageMaker built-in options should the specialist use to handle training of large model sizes?

An e-commerce company is designing a chatbot to assist customers with product inquiries, order status updates, and troubleshooting.

Which capability of AI is most relevant for ensuring that the chatbot provides real-time responses to customer queries?

A company uses a generative AI model to automate content creation for its social media posts. The model has been trained on various topics, including technology, fashion, and travel. Recently, the company decided to expand its business into the fitness industry.

Which capability of generative AI will be crucial for the model to adjust its output and generate relevant fitness-related content?

A technology firm is implementing a new generative AI model for customer interactions and needs to ensure the system’s security against various vulnerabilities. The ML security team is tasked with identifying the most critical security vulnerabilities that could impact the AI model’s performance and integrity.

Which vulnerabilities should the firm prioritize? (Select THREE.)

An ML specialist has created a foundation model for a customer support chatbot. The bot’s responses are accurate but don’t align with the company’s formatting. The specialist wants to adjust the responses to match the company’s branding without high costs.

Which method will fulfill these requirements in the most cost-efficient manner?

A company is testing a model for generating text summaries and needs a metric to evaluate how well the summaries match human-created references.

Which metric is most appropriate for this evaluation?

An insurance company receives many paper-based claim forms from policyholders. These forms contain handwritten and printed information about accidents, medical treatments, and property damage. The company wants to automate the extraction of relevant data from these scanned documents to streamline its claims processing workflow.

Which AWS service should you recommend to achieve this goal?

A company has a recommender system that generates embeddings from customer interaction data. They want to improve the speed and efficiency of retrieving similar product recommendations.

Which AWS services are best suited for implementing vector search to optimize the recommendation system? (Select THREE.)

A company is considering implementing generative AI models to enhance its customer support system. However, the technical team is concerned about the potential disadvantages and limitations of using such models in production. They need to identify the specific challenges that may arise when working with generative AI.

What are some common challenges or drawbacks associated with using generative AI models? (Select TWO.)

A financial company has collected 2 years of daily transaction data stored in an Amazon S3 bucket. To enhance liquidity management, financial planning, and resource allocation, they plan to develop a machine-learning model to forecast transaction volumes for the next 90 days.

Which type of algorithm should the company use?

A financial company is using an AI model to identify potential loan defaults. To ensure the model works well in production, they must set up processes for capturing real-time data, comparing it with the training set, detecting performance issues, and generating alerts.

Which stage of the model development pipeline should the company focus on?

A company is building a mobile application that assists visually impaired users. The app must be able to convert printed text from images into spoken language. Users can take pictures of documents, handwritten notes, or product labels, and the app will read the content aloud. The application needs to be accurate, reliable, and efficient.

Which AWS services would you recommend for implementing this functionality? (Select TWO.)

A legal firm has a large collection of scanned legal documents and case files in PDF format. They need a system to automate text extraction, identify key elements like tables and forms, and analyze image content to minimize manual intervention.

Which AWS services will most efficiently meet the firm’s needs with LEAST operational management? (Select TWO.)

A retail company sells electronic products online and is facing inventory management issues. They want to implement a demand prediction model to address this problem.

Which stage in implementing the model is most critical for addressing stockouts and overstock situations?

An e-commerce company uses Amazon SageMaker to build an ML model for customer review segmentation. They need a feature for efficient data cleansing and preparation with minimal coding.

Which SageMaker feature should they use?

A retail company wants a chatbot to assist customers with product recommendations and order inquiries. The chatbot must use the product catalog and order history stored in Amazon S3. The company needs a fully managed service that handles natural language understanding, model selection, and conversation flow with minimal setup and maintenance.

Which AWS service would be the MOST suitable choice for this use case?

A development team is building a social media platform that allows users to upload images. They want to ensure that inappropriate content is filtered out.

Which Amazon Rekognition API can detect unsafe content in a specified JPEG or PNG format image?

A cloud security engineer is tasked with securing machine learning (ML) workloads in an AWS environment. The engineer needs to ensure that only specific applications and services can access Amazon SageMaker and Amazon RDS resources. These applications require controlled and limited access to these services to maintain security and minimize the risk of unauthorized access.

Which AWS service or feature can the engineer use to grant and manage these permissions effectively?

A cybersecurity firm is deploying an ML model to analyze network traffic for security threats. The firm must provide detailed documentation of the model’s training and ensure its predictions are fully explainable for audits.

Which of the following combinations of Amazon SageMaker features will fulfill these requirements? (Select TWO.)

A company needs to label a large dataset of images with high accuracy to train a machine learning model. The company requires a solution combining human labeling with machine learning to ensure data quality.

Which AWS service or feature will best meet this requirement?

A company relies heavily on machine learning models for personalized recommendations and fraud detection. The company stores sensitive data in Amazon S3 buckets and needs a solution that automatically discovers, classifies, and protects this sensitive data.

Which of the following is the MOST suitable for this use case?

An e-commerce company is developing a model using Amazon SageMaker to forecast the probability of a product being returned after purchase. The company owns a labeled dataset containing product categories, prices, customer reviews, and return status stored in an Amazon S3 bucket.

What machine learning approach is most appropriate for this task?

A data scientist is evaluating a machine learning model and notices that it performs well on the training data but poorly on the test data.

Which combination of bias and variance is likely causing this issue?

An AI startup uses generative AI models to create personalized content. The company develops and deploys these AI models using Amazon Sagemaker, Amazon Bedrock, and Amazon Q Business. Recently, there have been concerns about unauthorized access to sensitive AI training data and model parameters.

Which of the following services can help the startup audit AWS Service API activity related to their generative AI workloads?

An organization plans to leverage generative AI to craft personalized marketing content for their campaigns.

Which foundational AI capability is essential to ensure generative AI’s effective and responsible use?

A travel agency needs to fine-tune a foundation model (FM) to assist customers by providing detailed trip planning advice, handling multi-turn conversations about travel preferences, and making personalized recommendations.

Which method will satisfy these requirements?

A project involves generating product descriptions for an e-commerce website using a dataset of existing product descriptions from the site.

Which fine-tuning approach is most appropriate for adapting a pre-trained language model to generate product descriptions similar to those in the dataset?

What term refers to a branch of AI that enables systems to learn and make predictions based on data without being explicitly structured?

A company is developing an application for document summarization using a large language model (LLM). They will use embeddings to help the model understand and process information more effectively.

Why are embeddings important for the LLM in generating accurate summaries?

An AI specialist is testing a chatbot that uses an embedding model to provide recommendations based on user input. The specialist types “good Japanese restaurants” into the chatbot.

What would the embedding model generate?

A Machine Learning Engineer is training a multi-classification model for predicting musical genres. The Specialist wants to evaluate model performance through a visual representation of different metrics.

Which visualization technique should the Engineer use?

An ML engineer is tasked with forecasting the monthly revenue for a subscription-based service.

Which evaluation metrics should be used to assess the model’s performance? (Select TWO.)

A data scientist is working on a machine learning model using Amazon SageMaker. The model performs poorly on the training and validation datasets, showing high bias.
What is the most likely cause of this issue?

An AI specialist is developing a system to detect vehicles in street images using machine learning. The goal is to create labels for a large dataset of street images and utilize Reinforcement Learning from Human Feedback (RLHF) to improve the model over time.

Which of the following options would be the most suitable for this task?

An AI Specialist implements AI models to optimize a company’s network operations. To comply with industry standards, the specialist must document the models’ training and performance details for auditing purposes.

What AWS service can help the company fulfill this need?

A marketing team plans to use Amazon Bedrock to generate personalized email content for different customer segments.

What should the team do FIRST to get started with Amazon Bedrock?

A financial institution must ensure that data transferred from Amazon S3 to an Amazon SageMaker instance for training machine learning models does not leave the AWS network, adhering to strict compliance requirements.

Which AWS Service will meet this requirement most effectively?

A team is working on a machine learning project. They have developed a model for predicting whether an email is spam or not. Before deploying the model, the team wants to ensure fairness and transparency.

Which options would be the most suitable for this use case?

A biotech company uses machine learning (ML) models on AWS to analyze sensitive genomic data. Before continuing its research, the company must review AWS’s adherence to industry data security and regulatory compliance regulations.

Which service can provide this information?

An organization is developing a conversational AI assistant using a large language model. The organization wants to incorporate human feedback to improve the model’s responses and ensure they are appropriate and helpful.

Which steps are part of the RLHF (Reinforcement Learning from Human Feedback) approach? (Select TWO.)

A retail organization is building a machine-learning model for its customer support chatbot. They need to evaluate how closely the chatbot’s responses match those of subject matter experts. The organization also wants to optimize the chatbot’s speed of response.

What is the most appropriate metric to evaluate the chatbot’s response similarity to expert answers?

An ML engineer is working on a machine learning project. The engineer has trained several models using different algorithms and hyperparameters. These models need to be efficiently managed for deployment in a production environment.

Which service should be used to catalog models, manage model versions, and associate metadata with the models?