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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. After completing this module, students will be able to:

• 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 AI Services
• Understand capabilities of the Azure Bot Service
• Understand capabilities of Azure Cognitive Search

Module 2: Create and consume Azure AI Services Azure AI Services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services. After completing this module, students will be able to:

• Provision Azure AI Services resources in an Azure subscription
• Identify endpoints, keys, and locations required to consume an Azure AI Services resource
• Use a REST API to consume an Azure AI service
• Use an SDK to consume an Azure AI service

Module 3: Secure Azure AI Services Securing Azure AI Services can help prevent data loss and privacy violations for user data that may be a part of the solution. After completing this module, students will be able to:

• Consider authentication for Azure AI Services
• Manage network security for Azure AI Services

Module 4: Monitor Azure AI Services Azure AI Services enable you to integrate artificial intelligence into your applications and services. It's important to be able to monitor Azure AI Services in order to track utilization, determine trends, and detect and troubleshoot issues. After completing this module, students will be able to:

• Monitor Azure AI Services costs
• Create alerts
• View metrics
• Manage diagnostic logging

Module 5: Deploy Azure AI services in containers Learn about Container support in Azure AI Services allowing the use of APIs available in Azure and enable flexibility in where to deploy and host the services with Docker containers. After completing this module, students will be able to:

• Create Containers for Reuse
• Deploy to a Container
• Secure a Container
• Consume Azure AI Services from a Container

Module 6: Extract insights from text with the Azure AI Language service The Azure AI Language service enables you to create intelligent apps and services that extract semantic information from text. After completing this module, students will be able to:

• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities

Module 7: Translate text with the Azure AI Translator service The Azure AI Translator service enables you to create intelligent apps and services that can translate text between languages. After completing this module, students will be able to:

• Provision an Azure AI Translator resource
• Understand language detection, translation, and transliteration
• Specify translation options
• Define custom translations

Module 8: Create speech-enabled apps with Azure AI services The Azure AI 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. After completing this module, students will be able to:

• Provision an Azure resource for the Azure AI Speech service
• Use the Azure AI 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 Azure AI 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. After completing this module, students will be able to:

• Provision Azure resources for speech translation
• Generate text translation from speech
• Synthesize spoken translations

Module 10: Build a conversational language understanding model The Azure AI Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language. After completing this module, students will be able to:

• Provision Azure resources for Azure AI Language resource
• Define intents, utterances, and entities
• Use patterns to differentiate similar utterances
• Use pre-built entity components
• Train, test, publish, and review an Azure AI Language model

Module 11: Develop an app with Azure AI Language After creating an Azure AI Language Understanding model, you can publish it and consume it from client applications. After completing this module, students will be able to:

• Understand capabilities of an Azure AI Language Understanding model
• Process predictions from an Azure AI Language in your app

Module 12: Build a question answering solution The question answering capability of the Azure AI Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers. After completing this module, students will be able to:

• 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. After completing this module, students will be able to:

• 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. After completing this module, students will be able to: Understand dialogs

• Plan conversational flow
• Design the user experience
• Create a bot with the Bot Framework Composer

Module 15: Analyze images With the Azure AI Vision service, you can use pre-trained models to analyze images and extract insights and information from them. After completing this module, students will be able to:

• Provision an Azure AI Vision resource
• Analyze an image
• Generate a smart-cropped thumbnail

Module 16: Analyze video Azure Video Indexer is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more. After completing this module, students will be able to:

• Describe Azure Video Indexer capabilities
• Extract custom insights
• Use Azure Video Indexer widgets and APIs

Module 17: Classify images Image classification is used to determine the main subject of an image. You can use the Azure AI Custom Vision services to train a model that classifies images based on your own categorizations. After completing this module, students will be able to:

• Provision Azure resources for Azure AI 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 Azure AI Custom Vision to train a model to detect specific classes of object in images. After completing this module, students will be able to:

• Provision Azure resources for Azure AI 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. After completing this module, students will be able to:

• Identify options for face detection, analysis, and identification
• Understand considerations for face analysis
• Detect faces with the Azure AI 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 Azure AI Vision Service Azure's Azure AI 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). After completing this module, students will be able to:

• Read text from images with the Read API
• Use the Azure AI 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 Azure Document Intelligence Azure Document Intelligence 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 Document Intelligence Azure AI service. After completing this module, students will be able to:

• Identify how Azure Document Intelligence's layout service, prebuilt models, and custom service can automate processes
• Use Azure Document Intelligence's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Azure Document Intelligence 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. After completing this module, students will be able to:

• 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. After completing this module, students will be able to:

• 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. After completing this module, students will be able to:

• Create a knowledge store from an Azure Cognitive Search pipeline
• View data in projections in a knowledge store

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