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所在平台: Udemy |
课程主页: https://www.udemy.com/course/prep-tests-azure-ai-engineer-associate-exam-ai-102/
课程评论：没有评论
课程名称：Prep Tests: Azure AI Engineer Associate Exam AI-102 课程概述： 本课程旨在为考取Azure AI Engineer Associate认证的候选人提供所需的知识与技能。候选人需要构建、管理和部署利用Azure认知服务和应用AI服务的AI解决方案。他们的职责包括参与AI解决方案开发的各个阶段，从需求定义、设计到开发、部署、维护、性能调整和监控。他们与解决方案架构师合作，将愿景转化为实用方案，并与数据科学家、数据工程师、物联网专家和AI开发人员合作，构建完整的端到端AI解决方案。 候选人应熟练掌握C#或Python，并能够使用基于REST的API和SDK在Azure上构建计算机视觉、自然语言处理、知识挖掘和对话AI解决方案。此外，他们需要了解Azure AI产品组合的组成部分及可用的数据存储选项，同时理解并能应用负责任的AI原则。 核心技能： - 规划和管理Azure认知服务解决方案 - 实施计算机视觉解决方案 - 实施自然语言处理解决方案 - 实施知识挖掘解决方案 - 实施对话AI解决方案 考试内容将涵盖以下模块/主题： 1. 规划和管理Azure认知服务解决方案（15-20%） - 选择合适的认知服务资源 - 规划和配置认知服务解决方案的安全性 - 创建认知服务资源 - 规划和实施认知服务容器 2. 实施计算机视觉解决方案（20-25%） - 使用计算机视觉API分析图像 - 从图像中提取文本 - 提取图像中的面部信息 - 使用自定义视觉服务实施图像分类 - 使用自定义视觉服务实施物体检测解决方案 - 使用Azure视频分析器分析视频 3. 实施自然语言处理解决方案（20-25%） - 使用文本分析服务分析文本 - 使用语音服务管理语音 - 进行语言翻译 - 使用语言理解服务（LUIS）构建初步语言模型 - 基于LUIS迭代和优化语言模型 - 管理LUIS模型 4. 实施知识挖掘解决方案（15-20%） - 实施认知搜索解决方案 - 实施丰富管道 - 实施知识存储 - 管理认知搜索解决方案 - 管理索引 5. 实施对话AI解决方案（15-20%） - 使用QnA Maker创建知识库 - 设计和实现对话流程 - 使用Bot Framework SDK创建机器人 - 使用Bot Framework Composer创建机器人 - 将认知服务集成到机器人中 本课程为希望掌握Azure AI解决方案设计与实施的专业人士提供了全面的知识背景和技能。通过学习该课程，学员能够更好地为AI-102考试做好准备。
Candidates for the Azure AI Engineer Associate certification build, manage, and deploy AI solutions that leverage Azure Cognitive Services and Azure Applied AI services.Their responsibilities include participating in all phases of AI solutions development-from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.Candidates for this certification should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.Skills measuredPlan and manage an Azure Cognitive Services solutionImplement Computer Vision solutionsImplement natural language processing solutionsImplement knowledge mining solutionsImplement conversational AI solutionsThe Exam consists of questions covering the following modules/topics:- Plan and Manage an Azure Cognitive Services Solution (15-20%)Select the appropriate Cognitive Services resourcePlan and configure security for a Cognitive Services solutionCreate a Cognitive Services resourcePlan and implement Cognitive Services containers- Implement Computer Vision Solutions (20-25%)Analyze images by using the Computer Vision APIExtract text from imagesExtract facial information from imagesImplement image classification by using the Custom Vision servicePortalImplement an object detection solution by using the Custom Vision serviceAnalyze video by using Azure Video Analyzer for Media (formerly Video Indexer)- Implement Natural Language Processing Solutions (20-25%)Analyze text by using the Text Analytics serviceManage speech by using the Speech serviceTranslate languageBuild an initial language model by using Language Understanding Service (LUIS)Iterate on and optimize a language model by using LUISManage a LUIS model- Implement Knowledge Mining Solutions (15-20%)Implement a Cognitive Search solutionImplement an enrichment pipelineImplement a knowledge storeManage a Cognitive Search solutionManage indexing- Implement Conversational AI Solutions (15-20%)Create a knowledge base by using QnA MakerDesign and implement conversation flowCreate a bot by using the Bot Framework SDKCreate a bot by using the Bot Framework ComposerIntegrate Cognitive Services into a bot
