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AI-102: Microsoft Azure AI Solution Practice Exam is a comprehensive and detailed resource designed to help individuals prepare for the Microsoft Azure AI Solution certification exam. This practice exam is specifically tailored to cover all the essential topics and skills required to successfully pass the exam and become a certified Azure AI Solution professional.This practice exam provides a realistic simulation of the actual certification exam, allowing candidates to familiarize themselves with the format, structure, and types of questions they can expect to encounter. It includes a wide range of questions that assess the candidate's knowledge and understanding of various AI concepts, including machine learning, natural language processing, computer vision, and more.AI-102: Microsoft Azure AI Solution Practice Exam offers a comprehensive learning experience, providing detailed explanations and references for each question. This allows candidates to not only assess their knowledge but also learn from their mistakes and strengthen their understanding of the subject matter. Additionally, the practice exam includes timed sections to help candidates improve their time management skills and simulate the pressure of the actual exam environment. With this resource, individuals can confidently prepare for the Microsoft Azure AI Solution certification exam and enhance their career prospects in the field of AI and cloud computing.Microsoft Azure AI Solution Exam Summary:Exam Name: Microsoft Azure AI SolutionExam Code: AI-102Exam Price: 165 (USD)Number of Questions: Maximum of 40-60 questions,Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,Length of Test: 130 Minutes. The exam is available in English and Japanese languages.Passing Score: 700 / 1000Languages: English at launch. JapaneseSchedule Exam: Pearson VUEMicrosoft AI-102 Exam Syllabus Topics:Plan and manage an Azure AI solution (25-30%)Select the appropriate Azure AI serviceSelect the appropriate service for a vision solutionSelect the appropriate service for a language analysis solutionSelect the appropriate service for a decision support solutionSelect the appropriate service for a speech solutionSelect the appropriate Applied AI servicesPlan and configure security for Azure AI servicesManage account keysManage authentication for a resourceSecure services by using Azure Virtual NetworksPlan for a solution that meets Responsible AI principlesCreate and manage an Azure AI serviceCreate an Azure AI resourceConfigure diagnostic loggingManage costs for Azure AI servicesMonitor an Azure AI resourceDeploy Azure AI servicesDetermine a default endpoint for a serviceCreate a resource by using the Azure portalIntegrate Azure AI services into a continuous integration/continuous deployment (CI/CD) pipelinePlan a container deploymentImplement prebuilt containers in a connected environmentCreate solutions to detect anomalies and improve contentCreate a solution that uses Anomaly Detector, part of Cognitive ServicesCreate a solution that uses Azure Content Moderator, part of Cognitive ServicesCreate a solution that uses Personalizer, part of Cognitive ServicesCreate a solution that uses Azure Metrics Advisor, part of Azure Applied AI ServicesCreate a solution that uses Azure Immersive Reader, part of Azure Applied AI ServicesImplement image and video processing solutions (15-20%)Analyze imagesSelect appropriate visual features to meet image processing requirementsCreate an image processing request to include appropriate image analysis featuresInterpret image processing responsesExtract text from imagesExtract text from images or PDFs by using the Computer Vision serviceConvert handwritten text by using the Computer Vision serviceExtract information using prebuilt models in Azure Form RecognizerBuild and optimize a custom model for Azure Form RecognizerImplement image classification and object detection by using the Custom Vision service, part of Azure Cognitive ServicesChoose between image classification and object detection modelsSpecify model configuration options, including category, version, and compactLabel imagesTrain custom image models, including classifiers and detectorsManage training iterationsEvaluate model metricsPublish a trained iteration of a modelExport a model to run on a specific targetImplement a Custom Vision model as a Docker containerInterpret model responsesProcess videosProcess a video by using Azure Video IndexerExtract insights from a video or live stream by using Azure Video IndexerImplement content moderation by using Azure Video IndexerIntegrate a custom language model into Azure Video IndexerImplement natural language processing solutions (25-30%)Analyze textRetrieve and process key phrasesRetrieve and process entitiesRetrieve and process sentimentDetect the language used in textDetect personally identifiable information (PII)Process speechImplement and customize text-to-speechImplement and customize speech-to-textImprove text-to-speech by using SSML and Custom Neural VoiceImprove speech-to-text by using phrase lists and Custom SpeechImplement intent recognitionImplement keyword recognitionTranslate languageTranslate text and documents by using the Translator serviceImplement custom translation, including training, improving, and publishing a custom modelTranslate speech-to-speech by using the Speech serviceTranslate speech-to-text by using the Speech serviceTranslate to multiple languages simultaneouslyBuild and manage a language understanding modelCreate intents and add utterancesCreate entitiesTrain evaluate, deploy, and test a language understanding modelOptimize a Language Understanding (LUIS) modelIntegrate multiple language service models by using OrchestratorImport and export language understanding modelsCreate a question answering solutionCreate 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 solutionCreate a multi-domain question answering solutionUse metadata for question-and-answer pairsImplement knowledge mining solutions (5-10%)Implement a Cognitive Search solutionProvision a Cognitive Search resourceCreate data sourcesDefine an indexCreate and run an indexerQuery an index, including syntax, sorting, filtering, and wildcardsManage knowledge store projections, including file, object, and table projectionsApply AI enrichment skills to an indexer pipelineAttach a Cognitive Services account to a skillsetSelect and include built-in skills for documentsImplement custom skills and include them in a skillsetImplement incremental enrichmentImplement conversational AI solutions (15-20%)Design and implement conversation flowDesign conversational logic for a botChoose appropriate activity handlers, dialogs or topics, triggers, and state handling for a botBuild a conversational botCreate a bot from a templateCreate a bot from scratchImplement activity handlers, dialogs or topics, and triggersImplement channel-specific logicImplement Adaptive CardsImplement multi-language support in a botImplement multi-step conversationsManage state for a botIntegrate Cognitive Services into a bot, including question answering, language understanding,and Speech serviceTest, publish, and maintain a conversational botTest a bot using the Bot Framework Emulator or the Power Virtual Agents web appTest a bot in a channel-specific environmentTroubleshoot a conversational botDeploy bot logicAI-102: Microsoft Azure AI Solution is a powerful and comprehensive platform that enables businesses to leverage the capabilities of artificial intelligence. With its seamless integration with Microsoft Azure, businesses can harness the scalability, reliability, and security of the cloud to build, deploy, and manage AI applications. Whether it's leveraging pre-built AI models or creating custom solutions, this solution offers a wide range of features and functionalities to cater to various AI use cases.

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