Designing and Implementing a Microsoft Azure AI Solution Training (AI-102)

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 Microsoft Azure AI Solution Training course will use C# or Python as the programming language. Designing and Implementing a Microsoft Azure AI Solution Training (AI-102) Benefits In this course, you will learn how to: Understand AI Solution Requirements  Design AI Solutions  Build and Train AI Models  Deploy AI Models  Integrate AI Models into Applications  Monitor and Maintain AI Solutions  Work with Cognitive Services  Implement Natural Language Processing (NLP) Solutions  Build Conversational AI Solutions  Understand Responsible AI Practices  Security and Compliance in AI Solutions  Training Prerequisites If you are new to artificial intelligence, and want an overview of AI capabilities on Azure, consider completing Microsoft Azure AI Fundamentals Training (AI-900) before taking this one. You should already 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 Certification Information This course can help you prepare for the following Microsoft role-based certification exam — Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. Microsoft Azure AI Solution Training Outline Module 1: Prepare to develop AI solutions on Azure  As an aspiring Azure AI Engineer, you should understand core concepts and principles of AI development, and the capabilities of Azure services used in AI solutions.  Lessons  Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure Cognitive Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search Module 2: Create and consume Cognitive Services Azure Cognitive Services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services.  Lessons  Provision Cognitive Services resources in an Azure subscription. Identify endpoints, keys, and locations required to consume a Cognitive Services resource. Use a REST API to consume a cognitive service. Use an SDK to consume a cognitive service. Module 3: Secure Cognitive Services  Securing Cognitive Services can help prevent data loss and privacy violations for user data that may be a part of the solution.  Lessons  Consider authentication for Cognitive Services Manage network security for Cognitive Services Module 4: Monitor Cognitive Services  Azure Cognitive Services enable you to integrate artificial intelligence into your applications and services. It's important to be able to monitor Cognitive Services in order to track utilization, determine trends, and detect and troubleshoot issues.  Lessons  Monitor Cognitive Services costs Create alerts View metrics Manage diagnostic logging Module 5: Deploy cognitive services in containers  Learn about Container support in Cognitive Services allowing the use of APIs available in Azure and enable flexibility in where to deploy and host the services with Docker containers.  Lessons  Create Containers for Reuse Deploy to a Container Secure a Container Consume Cognitive Services from a Container Module 6: Extract insights from text with the Language service  The Language service enables you to create intelligent apps and services that extract semantic information from text.  Lessons  Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities Module 7: Translate text with the Translator service  The Translator service enables you to create intelligent apps and services that can translate text between languages.  Lessons  Provision a Translator resource Understand language detection, translation, and transliteration Specify translation options Define custom translations Module 8: Create speech-enabled apps with the Speech service  The Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text-to-speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.  Lessons  Provision an Azure resource for the Speech service Use the Speech to text API to implement speech recognition Use the Text to speech API to implement speech synthesis Configure audio format and voices Use Speech Synthesis Markup Language (SSML) Module 9: Translate speech with the speech service  Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages. Lessons Provision Azure resources for speech translation. Generate text translation from speech. Synthesize spoken translations. Module 10: Build a Language Understanding model  The Language Understanding service enables you to train a language model that apps can use to extract meaning from natural language.  Lessons  Provision Azure resources for Language Understanding Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a Language Understanding model Module 11: Publish and use a Language Understanding app After creating a Language Understanding app, you can publish it and consume it from client applications.  Lessons  Understand capabilities of a Language Understanding app Process predictions from a Language Understanding app Deploy a language-understanding app in a container Module 12: Build a question answering solution  The question-answering capability of the Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.  Lessons  Understand question answering Compare question answering to language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Consume a knowledge base Implement active learning Create a question-answering bot Module 13: Create a bot with the Bot Framework SDK  Learn how to build a bot by using the Microsoft Bot Framework SDK.  Lessons  Understand principles of bot design Use the Bot Framework SDK to build a bot Deploy a bot to Azure Module 14: Create a Bot with the Bot Framework Composer  User the Bot Framework Composer to quickly and easily build sophisticated conversational bots without writing code.   Lessons Understand dialogs  Plan conversational flow  Design the user experience  Create a bot with the Bot Framework Composer Module 15: Analyze images  With the Computer Vision service, you can use pre-trained models to analyze images and extract insights and information from them.   Lessons  Provision a Computer Vision resource Analyze an image Generate a smart-cropped thumbnail Module 16: Analyze video  Azure Video Analyzer for Media is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.  Lessons  Describe Video Analyzer for Media capabilities Extract custom insights Use Video Analyzer for Media widgets and APIs Module 17: Classify images Image classification is used to determine the main subject of an image. You can use the Custom Vision services to train a model that classifies images based on your own categorizations.  Lessons  Provision Azure resources for Custom Vision  Understand image classification  Train an image classifier Module 18: Detect objects in images Object detection is used to locate and identify objects in images. You can use Custom Vision to train a model to detect specific classes of object in images.  Lessons  Provision Azure resources for Custom Vision Understand object detection Train an object detector Consider options for labeling images Module 19: Detect, analyze, and recognize faces The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability. Lessons  Identify options for face detection, analysis, and identification Understand considerations for face analysis Detect faces with the Computer Vision service Understand capabilities of the Face service Compare and match detected faces Implement facial recognition Module 20: Read Text in Images and Documents with the Computer Vision Service Azure's Computer Vision service uses algorithms to process images and return information. This module teaches you how to use the Read API for optical character recognition (OCR). Lessons Read text from images with the Read API Use the Computer Vision service with SDKs and the REST API Develop an application that can read printed and handwritten text Module 21: Extract data from forms with Form Recognizer Form Recognizer uses machine learning technology to identify and extract key-value pairs and table data from form documents with accuracy, at scale. This module teaches you how to use the Azure Form Recognizer cognitive service. Lessons Identify how Form Recognizer's layout service, prebuilt models, and custom service can automate processes Use Form Recognizer's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Form Recognizer Studio Develop and test custom models Module 22: Create an Azure Cognitive Search Solution Unlock the hidden insights in your data with Azure Cognitive Search. Lessons Create an Azure Cognitive Search solution Develop a search application Module 23: Create a custom skill for Azure Cognitive Search  Use the power of artificial intelligence to enrich your data and find new insights. Lessons Implement a custom skill for Azure Cognitive Search Integrate a custom skill into an Azure Cognitive Search skillset Module 24: Create a knowledge store with Azure Cognitive Search Persist the output from an Azure Cognitive Search enrichment pipeline for independent analysis or downstream processing. Lessons Create a knowledge store from an Azure Cognitive Search pipeline View data in projections in a knowledge store