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Designing and Implementing an Azure AI Solution (AI-102)
Build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.One Microsoft exam voucher included with class.
After successfully completing this course, you will be able to:· Describe considerations for AI-enabled application development· Create, configure, deploy, and secure Azure Cognitive Services· Develop applications that analyze text· Develop speech-enabled applications· Create applications with natural language understanding capabilities· Create QnA applications· Create conversational solutions with bots· Use computer vision services to analyze images and videos· Create custom computer vision models· Develop applications that detect, analyze, and recognize faces· Develop applications that read and process text in images and documents· Create intelligent search solutions for knowledge mining
Module 1: Introduction to AI on AzureArtificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.LessonsIntroduction to Artificial IntelligenceArtificial Intelligence in AzureAfter completing this module, students will be able to:Describe considerations for creating AI-enabled applicationsIdentify Azure services for AI application developmentModule 2: Developing AI Apps with Cognitive ServicesCognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services.LessonsGetting Started with Cognitive ServicesUsing Cognitive Services for Enterprise ApplicationsAfter completing this module, students will be able to:Provision and consume cognitive services in AzureManage cognitive services securityMonitor cognitive servicesUse a cognitive services containerModule 3: Getting Started with Natural Language ProcessingNatural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.LessonsAnalyzing TextTranslating TextAfter completing this module, students will be able to:Use the Text Analytics cognitive service to analyze textUse the Translator cognitive service to translate textModule 4: Building Speech-Enabled ApplicationsMany modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.LessonsSpeech Recognition and SynthesisSpeech TranslationAfter completing this module, students will be able to:Use the Speech cognitive service to recognize and synthesize speechUse the Speech cognitive service to translate speechModule 5: Creating Language Understanding SolutionsTo build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.LessonsCreating a Language Understanding AppPublishing and Using a Language Understanding AppUsing Language Understanding with SpeechAfter completing this module, students will be able to:Create a Language Understanding appCreate a client application for Language UnderstandingIntegrate Language Understanding and SpeechModule 6: Building a QnA SolutionOne of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.LessonsCreating a QnA Knowledge BasePublishing and Using a QnA Knowledge BaseAfter completing this module, students will be able to:Use QnA Maker to create a knowledge baseUse a QnA knowledge base in an app or botModule 7: Conversational AI and the Azure Bot ServiceBots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
LessonsBot BasicsImplementing a Conversational BotAfter completing this module, students will be able to:Use the Bot Framework SDK to create a botUse the Bot Framework Composer to create a botModule 8: Getting Started with Computer VisionComputer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.LessonsAnalyzing ImagesAnalyzing VideosAfter completing this module, students will be able to:Use the Computer Vision service to analyze imagesUse Video Analyzer to analyze videosModule 9: Developing Custom Vision SolutionsWhile there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and how to use it to create custom image classification and object detection models.LessonsImage ClassificationObject DetectionAfter completing this module, students will be able to:Use the Custom Vision service to implement image classificationUse the Custom Vision service to implement object detectionModule 10: Detecting, Analyzing, and Recognizing FacesFacial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces.LessonsDetecting Faces with the Computer Vision ServiceUsing the Face ServiceAfter completing this module, students will be able to:Detect faces with the Computer Vision serviceDetect, analyze, and recognize faces with the Face serviceModule 11: Reading Text in Images and DocumentsOptical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.LessonsReading text with the Computer Vision ServiceExtracting Information from Forms with the Form Recognizer serviceAfter completing this module, students will be able to:Use the Computer Vision service to read text in images and documentsUse the Form Recognizer service to extract data from digital formsModule 12: Creating a Knowledge Mining SolutionUltimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.LessonsImplementing an Intelligent Search SolutionDeveloping Custom Skills for an Enrichment PipelineCreating a Knowledge StoreAfter completing this module, students will be able to:Create an intelligent search solution with Azure Cognitive SearchImplement a custom skill in an Azure Cognitive Search enrichment pipelineUse Azure Cognitive Search to create a knowledge store
Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution
Before attending this course, students must have:· Knowledge of Microsoft Azure and ability to navigate the Azure portal· Knowledge of either C# or Python· Familiarity with JSON and REST programming semantics
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