AI-102T00: Designing and Implementing a Microsoft Azure AI Solution Training Course

Module 1: Introduction to AI on Azure

Artificial Intelligence (AI) is becoming the backbone of modern applications and services. In this module, you will explore common AI capabilities that can be integrated into your apps and examine how these capabilities are realized within Microsoft Azure. You will also address key considerations for designing and implementing AI solutions with a focus on responsibility.

Lessons

• Introduction to Artificial Intelligence

• Artificial Intelligence in Azure

Upon completion of this module, students will be able to:

• Describe the key considerations for developing AI-enabled applications

• Identify the relevant Azure services for AI application development

Module 2: Developing AI Apps with Cognitive Services

Cognitive Services serve as the foundational components for integrating AI capabilities into your applications. In this module, you will learn the processes for provisioning, securing, monitoring, and deploying these cognitive services.

Lessons

• Getting Started with Cognitive Services

• Using Cognitive Services for Enterprise Applications

Lab: Get Started with Cognitive Services

Lab: Manage Cognitive Services Security

Lab: Monitor Cognitive Services

Lab: Use a Cognitive Services Container

Upon completion of this module, students will be able to:

• Provision and consume cognitive services within Azure

• Manage the security of cognitive services

• Monitor the performance and usage of cognitive services

• Utilize cognitive services containers

Module 3: Getting Started with Natural Language Processing

Natural Language Processing (NLP) is a subset of artificial intelligence focused on extracting meaningful insights from written or spoken language. In this module, you will learn how to utilize cognitive services to analyze and translate text.

Lessons

• Analyzing Text

• Translating Text

Lab: Translate Text

Lab: Analyze Text

Upon completion of this module, students will be able to:

• Employ the Text Analytics cognitive service for text analysis

• Utilize the Translator cognitive service for text translation

Module 4: Building Speech-Enabled Applications

Many contemporary applications and services support spoken input and can respond by synthesizing speech. This module continues the exploration of natural language processing by teaching you how to construct speech-enabled applications.

Lessons

• Speech Recognition and Synthesis

• Speech Translation

Lab: Recognize and Synthesize Speech

Lab: Translate Speech

Upon completion of this module, students will be able to:

• Use the Speech cognitive service to recognize and synthesize audio

• Apply the Speech cognitive service for speech translation

Module 5: Creating Language Understanding Solutions

To build an application that intelligently understands and responds to natural language input, you must define and train a model for language understanding. In this module, you will learn how to leverage the Language Understanding service to create an app that can identify user intent from natural language input.

Lessons

• Creating a Language Understanding App

• Publishing and Using a Language Understanding App

• Using Language Understanding with Speech

Lab: Create a Language Understanding Client Application

Lab: Create a Language Understanding App

Lab: Use the Speech and Language Understanding Services

Upon completion of this module, students will be able to:

• Create a Language Understanding application

• Develop a client application for Language Understanding

• Integrate Language Understanding with Speech services

Module 6: Building a QnA Solution

A common interaction pattern between users and AI agents involves users submitting questions in natural language, to which the AI agent responds with an appropriate answer. In this module, you will explore how the QnA Maker service facilitates the development of such solutions.

Lessons

• Creating a QnA Knowledge Base

• Publishing and Using a QnA Knowledge Base

Lab: Create a QnA Solution

Upon completion of this module, students will be able to:

• Use QnA Maker to build a knowledge base

• Implement a QnA knowledge base within an app or bot

Module 7: Conversational AI and the Azure Bot Service

Bots form the basis of an increasingly prevalent type of AI application, where users engage in conversations with AI agents, often mirroring interactions with humans. In this module, you will explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a robust platform for creating and delivering conversational experiences.

Lessons

• Bot Basics

• Implementing a Conversational Bot

Lab: Create a Bot with the Bot Framework SDK

Lab: Create a Bot with Bot Framework Composer

Upon completion of this module, students will be able to:

• Develop a bot using the Bot Framework SDK

• Create a bot using the Bot Framework Composer

Module 8: Getting Started with Computer Vision

Computer vision is a field of artificial intelligence where software applications interpret visual input from images or video. In this module, you will begin your journey into computer vision by learning how to use cognitive services to analyze images and video.

Lessons

• Analyzing Images

• Analyzing Videos

Lab: Analyze Video

Lab: Analyze Images with Computer Vision

Upon completion of this module, students will be able to:

• Use the Computer Vision service to analyze images

• Employ the Video Analyzer to analyze video content

Module 9: Developing Custom Vision Solutions

While pre-defined general computer vision capabilities are useful in many scenarios, there are instances where you need to train a custom model using your own visual data. In this module, you will explore the Custom Vision service and learn how to use it to create custom image classification and object detection models.

Lessons

• Image Classification

• Object Detection

Lab: Classify Images with Custom Vision

Lab: Detect Objects in Images with Custom Vision

Upon completion of this module, students will be able to:

• Implement image classification using the Custom Vision service

• Implement object detection using the Custom Vision service

Module 10: Detecting, Analyzing, and Recognizing Faces

Facial detection, analysis, and recognition are standard computer vision scenarios. In this module, you will explore how to use cognitive services to identify human faces.

Lessons

• Detecting Faces with the Computer Vision Service

• Using the Face Service

Lab: Detect, Analyze, and Recognize Faces

Upon completion of this module, students will be able to:

• Detect faces using the Computer Vision service

• Detect, analyze, and recognize faces using the Face service

Module 11: Reading Text in Images and Documents

Optical character recognition (OCR) is another common computer vision scenario, where software extracts text from images or documents. In this module, you will explore cognitive services capable of detecting and reading text in images, documents, and forms.

Lessons

• Reading text with the Computer Vision Service

• Extracting Information from Forms with the Form Recognizer service

Lab: Read Text in Images

Lab: Extract Data from Forms

Upon completion of this module, students will be able to:

• Use the Computer Vision service to read text from images and documents

• Use the Form Recognizer service to extract data from digital forms

Module 12: Creating a Knowledge Mining Solution

Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly vital approach for building intelligent search solutions that use AI to extract insights from large repositories of digital data, enabling users to find and analyze those insights.

Lessons

• Implementing an Intelligent Search Solution

• Developing Custom Skills for an Enrichment Pipeline

• Creating a Knowledge Store

Lab: Create a Custom Skill for Azure Cognitive Search

Lab: Create an Azure Cognitive Search solution

Lab: Create a Knowledge Store with Azure Cognitive Search

Upon completion of this module, students will be able to:

• Create an intelligent search solution using Azure Cognitive Search

• Implement a custom skill within an Azure Cognitive Search enrichment pipeline

• Use Azure Cognitive Search to create a knowledge store