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The "AI-102 Azure AI Engineer Associate AI-102 PT Practice Test" offers you a unique opportunity to prepare comprehensively and practically for the AI-102 certification exam, which qualifies you as an Azure AI Engineer Associate. This practice test has been specially designed to provide a complete immersion in essential topics related to artificial intelligence engineering in the Azure environment.By participating in this practice test, you will have access to a series of carefully selected questions that address the most relevant concepts and scenarios for artificial intelligence engineering in Azure. Each question not only tests your knowledge but also challenges you to apply that knowledge in practical situations, similar to what you will encounter in the real world.Candidates for the AI-102 Exam: Designing and implementing a Microsoft Azure Ai Solution Build, manage and deploy AI solutions that enjoy Azure's cognitive services, Azure cognitive research and Microsoft Bot structure.Skills measured:Plan and manage an Azure AI solution (15-20%)Implement content moderation solutions (10-15%)Implement computer vision solutions (15-20%)Implement natural language processing solutions (30-35%)Implement knowledge mining and document intelligence solutions (10-15%)Implement generative AI solutions (10-15%)The Exam consists of questions covering the following modules/topics:Plan and manage an Azure AI solution (15-20%)Select the appropriate Azure AI serviceSelect the appropriate service for a computer vision solutionSelect the appropriate service for a natural language processing solutionSelect the appropriate service for a speech solutionSelect the appropriate service for a generative AI solutionSelect the appropriate service for a document intelligence solutionSelect the appropriate service for a knowledge mining solutionPlan, create and deploy an Azure AI servicePlan for a solution that meets Responsible AI principlesCreate an Azure AI resourceDetermine a default endpoint for a serviceIntegrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipelinePlan and implement a container deploymentManage, monitor, and secure an Azure AI serviceConfigure diagnostic loggingMonitor an Azure AI resourceManage costs for Azure AI servicesManage account keysProtect account keys by using Azure Key VaultManage authentication for an Azure AI Service resourceManage private communicationsImplement content moderation solutions (10-15%)Create solutions for content deliveryImplement a text moderation solution with Azure AI Content SafetyImplement an image moderation solution with Azure AI Content SafetyImplement computer vision solutions (15-20%)Analyze imagesSelect visual features to meet image processing requirementsDetect objects in images and generate image tagsInclude image analysis features in an image processing requestInterpret image processing responsesExtract text from images using Azure AI VisionConvert handwritten text using Azure AI VisionImplement custom computer vision models by using Azure AI VisionChoose between image classification and object detection modelsLabel imagesTrain a custom image model, including image classification and object detectionEvaluate custom vision model metricsPublish a custom vision modelConsume a custom vision modelAnalyze videosUse Azure AI Video Indexer to extract insights from a video or live streamUse Azure AI Vision Spatial Analysis to detect presence and movement of people in videoImplement natural language processing solutions (30-35%)Analyze text by using Azure AI LanguageExtract key phrasesExtract entitiesDetermine sentiment of textDetect the language used in textDetect personally identifiable information (PII) in textProcess speech by using Azure AI SpeechImplement text-to-speechImplement speech-to-textImprove text-to-speech by using Speech Synthesis Markup Language (SSML)Implement custom speech solutionsImplement intent recognitionImplement keyword recognitionTranslate languageTranslate text and documents by using the Azure AI Translator serviceImplement custom translation, including training, improving, and publishing a custom modelTranslate speech-to-speech by using the Azure AI Speech serviceTranslate speech-to-text by using the Azure AI Speech serviceTranslate to multiple languages simultaneouslyImplement and manage a language understanding model by using Azure AI LanguageCreate intents and add utterancesCreate entitiesTrain, evaluate, deploy, and test a language understanding modelOptimize a language understanding modelConsume a language model from a client applicationBackup and recover language understanding modelsCreate a question answering solution by using Azure AI LanguageCreate a question answering projectAdd question-and-answer pairs manuallyImport sourcesTrain and test a knowledge basePublish a knowledge baseCreate a multi-turn conversationAdd alternate phrasingAdd chit-chat to a knowledge baseExport a knowledge baseCreate a multi-language question answering solutionImplement knowledge mining and document intelligence solutions (10-15%)Implement an Azure AI Search solutionProvision an Azure AI Search resourceCreate data sourcesCreate an indexDefine a skillsetImplement custom skills and include them in a skillsetCreate and run an indexerQuery an index, including syntax, sorting, filtering, and wildcardsManage Knowledge Store projections, including file, object, and table projectionsImplement an Azure AI Document Intelligence solutionProvision a Document Intelligence resourceUse prebuilt models to extract data from documentsImplement a custom document intelligence modelTrain, test, and publish a custom document intelligence modelCreate a composed document intelligence modelImplement a document intelligence model as a custom Azure AI Search skillImplement generative AI solutions (10-15%)Use Azure OpenAI Service to generate contentProvision an Azure OpenAI Service resourceSelect and deploy an Azure OpenAI modelSubmit prompts to generate natural languageSubmit prompts to generate codeUse the DALL-E model to generate imagesUse Azure OpenAI APIs to submit prompts and receive responsesOptimize generative AIConfigure parameters to control generative behaviorApply prompt engineering techniques to improve responsesUse your own data with an Azure OpenAI modelFine-tune an Azure OpenAI modelMicrosoft Azure AI engineers build, manage, and deploy AI solutions that make the most of Azure Cognitive Services and Azure services. Their responsibilities include participating in all phases of AI solutions development from requirements definition and design to development, deployment, integration, maintenance, performance tuning, and monitoring.These professionals work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, infrastructure administrators, and other software developers to build complete end-to-end AI solutions.

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