AIF-C01-EXT-04_在线真题试卷与模拟练习_AIF-C01-EXT-04

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A healthcare company wants to extract relevant health information from unstructured clinical data such as physician's notes, discharge summaries, and test results from multiple hospitals.

Which ML-powered AWS service is the right fit to extract this data?

A business needs an automated solution that can extract text from thousands of receipts and invoices generated across all its stores.

Which AWS Machine Learning (ML) service can offer the most optimal solution for this use case ?

Which of the following use cases is addressed by Amazon Personalize?

A retail company wants to simplify how its employees access and analyze sales data stored in a large database. To achieve this, the company aims to implement a solution that automatically converts plain English text commands, such as "show total sales for the last quarter" or "list top-selling products," into SQL queries. This would allow employees without technical skills to interact with the database seamlessly, improving efficiency and decision-making.

Which of the following solutions would be most suitable for this purpose?

A technology company is exploring AWS DeepRacer to introduce its employees to machine learning through an engaging and hands-on platform. The team wants to understand the key features and capabilities of AWS DeepRacer. Which of the following represents the CORRECT statement about AWS DeepRacer?

A retail company is developing a machine learning model to improve its customer segmentation and targeting strategies. The data science team is working with both labeled and unlabeled customer data to train their models but needs to clearly understand the distinction between these two types of data to decide how best to use them. Understanding this difference is critical for selecting the appropriate machine learning techniques, such as supervised or unsupervised learning, for different stages of the project.

What is a key difference between labeled data and unlabeled data in the context of machine learning?

A healthcare company is using machine learning models in Amazon SageMaker to predict patient outcomes based on various health indicators. To comply with regulatory requirements and build trust with medical professionals, the company needs to understand and explain how different input features, such as age, blood pressure, and medical history, contribute to the model’s predictions. The company is exploring which Amazon SageMaker service can provide this level of transparency and interpretability for their machine learning models.

Which Amazon SageMaker service will help the company understand how an input feature contributes to the predictions of a machine learning model?

A tech company is building machine learning models using Amazon SageMaker Studio and wants to streamline its development process. The data science team prefers using familiar Integrated Development Environments (IDEs) to write, test, and debug code more efficiently. To ensure a smooth workflow, the team is exploring which IDEs are supported within SageMaker Studio to maximize productivity and compatibility with their existing tools.

Which of the following address the given requirement?

A healthcare analytics company is developing a machine learning model to provide patient risk assessments based on incoming medical data. The team needs to deploy the model in a way that supports continuous, low-latency predictions, where each request receives a response immediately, such as during patient check-ins. The team is evaluating deployment options within Amazon SageMaker and needs a solution that offers persistent endpoints to handle these individual prediction requests.

What do you recommend?

A company has recently migrated to AWS Cloud and it wants to optimize the hardware used for its AI workflows.

Which of the following would you suggest?

A retail company is seeking to empower its business analysts to create data-driven dashboards without needing technical expertise in coding or data query languages. The company wants a solution that allows analysts to use natural language to generate reports, visualize key metrics, and build Business Intelligence (BI) dashboards to inform decision-making across departments. They are exploring options within AWS that can help streamline this process for non-technical users.

Which of the following solutions allows business analysts to use natural language to build BI dashboards?

A financial services company is developing several machine learning models to handle fraud detection, credit scoring, and customer segmentation. To ensure consistent use of data and foster collaboration among its data scientists, the company needs an efficient way to share and manage the variables used in these models across different teams and projects. The goal is to create a centralized repository where these variables can be accessed and reused to maintain uniformity, reduce redundancy, and improve productivity.

Which of the following AWS tools would be the most suitable for achieving this objective?

A wildlife research organization has gathered thousands of images from camera traps in natural reserves worldwide, capturing various animal species. To support their research and conservation efforts, the organization wants to build a system that can automatically identify and categorize each animal in these images accurately and efficiently. The organization is evaluating different AI and machine learning techniques to achieve this goal.

Which approach would you suggest to effectively recognize and categorize the various animal species in their image dataset?

A company is creating a custom search solution that will bring together the company's data repositories, FAQs, and support tickets. The support tickets might contain personally identifiable information (PII) that needs to be redacted before the tickets are processed to create the search indexes.

Which AWS service will help you redact the PII in support tickets?

A financial services company is developing machine learning models using Amazon SageMaker to automate loan approvals and fraud detection. To ensure transparency and compliance with industry regulations, the data science team needs a tool that documents the model’s intended uses, performance metrics, and any assumptions made during development. This documentation is crucial for maintaining accountability and ensuring that the models are used appropriately.

Which Amazon SageMaker tool meets these requirements?

Which AWS service is specifically designed for converting medical speech to text, ensuring compliance with healthcare regulations such as HIPAA?

A financial services company is building machine learning models on AWS to automate loan approval processes. As an AI Practitioner, you have been tasked to build and maintain data lineage in the context of these machine learning models on AWS.

Which of the following would you identify as the key reason to maintain data lineage?

A software development team is exploring tools to improve their coding efficiency and streamline their workflow. They are particularly interested in leveraging Amazon Q Developer to support their development processes, but they want to understand its specific capabilities.

Which of the following accurately describes what Amazon Q Developer can do to enhance the team's development efforts?

A retail company is exploring the use of generative AI to improve its customer experience by personalizing recommendations and automating product descriptions. The company is interested in leveraging pre-built, high-performing Foundation Models (FMs) to accelerate development but also needs the ability to customize these models with its proprietary data to meet specific business needs. The company is seeking an AWS service that not only provides access to a variety of Foundation Models but also offers the option to privately fine-tune and customize these models for their unique use case.

Which AWS service/feature offers a choice of high-performing Foundation Models (FMs) and the ability to privately customize the FMs with your data?

Which AWS service helps you set up a cloud contact center in just a few clicks and onboard agents to help customers?

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