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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practice-exams-microsoft-azure-ai-100-azure-ai-engineer/
课程评论:没有评论
课程名称:实践考试 Microsoft Azure AI-102 Azure AI 解决方案 课程概述:本课程提供练习考试,旨在帮助学生为 Microsoft Azure AI-102 官方考试做好准备。需要注意的是,这些问题并不是官方考试中的正式问题,而是涵盖了相关知识领域的所有内容。许多问题基于虚构场景,并在其中涉及提问。考试知识要求会定期审查,以确保练习问题的内容包含最新的要求,因此内容可能会随时更新并且不提供提前通知。每道题都有详细的解答和参考材料链接,以确保问题解决的准确性。每次测试时,问题都会随机排列,因此学员需要理解答案的正确性,而不仅仅是记住上次测试中正确答案的选项。 作为 Microsoft Azure AI 工程师,学员的职责包括参与 AI 解决方案开发的各个阶段,包括需求定义、设计、开发、部署、集成、维护、性能调优和监控。学员需与解决方案架构师、数据科学家、数据工程师、物联网专家、基础设施管理员及其他软件开发人员合作,构建完整且安全的端到端 AI 解决方案,集成 AI 能力于其他应用和解决方案。 此课程的主要内容和技能概述包括: 1. 规划和管理 Azure AI 解决方案(15-20%) 2. 实施内容审核解决方案(10-15%) 3. 实施计算机视觉解决方案(15-20%) 4. 实施自然语言处理解决方案(30-35%) 5. 实施知识挖掘和文档智能解决方案(10-15%) 6. 实施生成式 AI 解决方案(10-15%) 课程还包括使用 Python 和 C# 开发解决方案的能力,以及使用表示性状态转移(REST)API 和 SDK,构建安全的图像处理、视频处理、自然语言处理、知识挖掘和生成式 AI 解决方案的知识。 总体而言,此课程旨在帮助学员巩固 Azure AI 相关的关键知识,并提高他们的实践能力,从而为正式的 Azure AI-102 考试做好充分准备。此课程不应成为学员的唯一学习材料,练习测试只是辅助主题学习材料的工具。
In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them.The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time.Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item "B" last time you went through the test.NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material.As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.Your responsibilities include participating in all phases of AI solutions development, including:Requirements definition and designDevelopmentDeploymentIntegrationMaintenancePerformance tuningMonitoringYou work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:Build complete and secure end-to-end AI solutions.Integrate AI capabilities in other applications and solutions.As an Azure AI engineer, you have experience developing solutions that use languages such as:PythonC#You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should:Understand the components that make up the Azure AI portfolio and the available data storage options.Be able to apply responsible AI principles.Skills at a glancePlan 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%)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 custom question answering solution by using Azure AI LanguageCreate a custom 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 responsesUse large multimodal models in Azure OpenAIOptimize 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 model