AWS Certified AI Practitioner

• #1

  Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?

  • AEmbeddings.
  • BTokens.
  • CModels.
  • DBinaries.
  解答を表示
• #2

  A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data. Which solution will meet these requirements?

  • AStore the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
  • BImport the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
  • CImport the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.
  • DImport the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
  解答を表示
• #3

  An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images. Which type of FM should the AI practitioner use to power the search application?

  • AMulti-modal embedding model.
  • BText embedding model.
  • CMulti-modal generation model.
  • DImage generation model.
  解答を表示
• #4

  A company is building a contact center application and wants to gain insights from customer conversations. The company wants to analyze and extract key information from the audio of the customer calls. Which solution meets these requirements?

  • ABuild a conversational chatbot by using Amazon Lex.
  • BTranscribe call recordings by using Amazon Transcribe.
  • CExtract information from call recordings by using Amazon SageMaker Model Monitor.
  • DCreate classification labels by using Amazon Comprehend.
  解答を表示
• #5

  A company wants to assess the costs that are associated with using a large language model (LLM) to generate inferences. The company wants to use Amazon Bedrock to build generative AI applications. Which factor will drive the inference costs?

  • ANumber of tokens consumed.
  • BTemperature value.
  • CAmount of data used to train the LLM.
  • DTotal training time.
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• #6

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

  • ADecision trees.
  • BLinear regression.
  • CLogistic regression.
  • DNeural networks.
  解答を表示
• #7

  A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model’s performance decreased significantly. What should the company do to mitigate this problem?

  • AReduce the volume of data that is used in training.
  • BAdd hyperparameters to the model.
  • CIncrease the volume of data that is used in training.
  • DIncrease the model training time.
  解答を表示
• #8

  A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly. Which evaluation metric should the company use to measure the model's performance?

  • AR-squared score.
  • BAccuracy.
  • CRoot mean squared error (RMSE).
  • DLearning rate.
  解答を表示
• #9

  A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions. Which business objective should the company use to evaluate the effect of the LLM chatbot?

  • AWebsite engagement rate.
  • BAverage call duration.
  • CCorporate social responsibility.
  • DRegulatory compliance.
  解答を表示
• #10

  A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information. Which action will reduce these risks?

  • ACreate a prompt template that teaches the LLM to detect attack patterns.
  • BIncrease the temperature parameter on invocation requests to the LLM.
  • CAvoid using LLMs that are not listed in Amazon SageMaker.
  • DDecrease the number of input tokens on invocations of the LLM.
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• #11

  A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible. Which solution will meet these requirements?

  • ADeploy optimized small language models (SLMs) on edge devices.
  • BDeploy optimized large language models (LLMs) on edge devices.
  • CIncorporate a centralized small language model (SLM) API for asynchronous communication with edge devices.
  • DIncorporate a centralized large language model (LLM) API for asynchronous communication with edge devices.
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• #12

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

  • AGenerative pre-trained transformers (GPT).
  • BResidual neural network.
  • CSupport vector machine.
  • DWaveNet.
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• #13

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

  • AReal-time inference.
  • BServerless inference.
  • CAsynchronous inference.
  • DBatch transform.
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• #14

  A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment. Which Amazon Bedrock pricing model meets these requirements?

  • AOn-Demand.
  • BModel customization.
  • CProvisioned Throughput.
  • DSpot Instance.
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• #15

  A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks. Which solution will meet this requirement?

  • AUse Amazon Inspector to monitor SageMaker Studio.
  • BUse Amazon Macie to monitor SageMaker Studio.
  • CConfigure SageMaker to use a VPC with an S3 endpoint.
  • DConfigure SageMaker to use S3 Glacier Deep Archive.
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• #16

  A company needs to build its own large language model (LLM) based on only the company’s private data. The company is concerned about the environmental effect of the training process. Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?

  • AAmazon EC2 C series.
  • BAmazon EC2 G series.
  • CAmazon EC2 P series.
  • DAmazon EC2 Trn series.
  解答を表示
• #17

  A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company’s product manuals. The manuals are stored as PDF files. Which solution meets these requirements MOST cost-effectively?

  • AUse prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.
  • BUse prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.
  • CUse all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.
  • DUpload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.
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• #18

  A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model. The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.Which solution will meet these requirements?

  • AUse Amazon SageMaker Serverless Inference to deploy the model.
  • BUse Amazon CloudFront to deploy the model.
  • CUse Amazon API Gateway to host the model and serve predictions.
  • DUse AWS Batch to host the model and serve predictions.
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• #19

  An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort. Which strategy meets these requirements?

  • AObject detection.
  • BAnomaly detection.
  • CNamed entity recognition.
  • DInpainting.
  解答を表示
• #20

  Which functionality does Amazon SageMaker Clarify provide?

  • AIntegrates a Retrieval Augmented Generation (RAG) workflow.
  • BMonitors the quality of ML models in production.
  • CDocuments critical details about ML models.
  • DIdentifies potential bias during data preparation.
  解答を表示

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