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

Module 1: Introduction to AI on Azure

Artificial Intelligence (AI) has become a central component of modern applications and services. In this module, you will explore common AI capabilities that can be integrated into your applications and understand how these capabilities are realized within Microsoft Azure. Additionally, you will examine key considerations for designing and implementing AI solutions responsibly.

Lessons

• Introduction to Artificial Intelligence

• Artificial Intelligence in Azure

Upon completing this module, learners will be able to:

• Outline considerations for developing AI-enabled applications

• Identify Azure services suitable for AI application development

Module 2: Developing AI Apps with Cognitive Services

Cognitive Services serve as the foundational building blocks for embedding AI capabilities into 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 completing this module, learners will be able to:

• Provision and consume cognitive services within Azure

• Manage security for 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 branch of artificial intelligence focused on deriving insights from written or spoken language. In this module, you will learn how to leverage cognitive services to analyze and translate text.

Lessons

• Analyzing Text

• Translating Text

Lab: Translate Text

Lab: Analyze Text

Upon completing this module, learners will be able to:

• Apply the Text Analytics cognitive service for text analysis

• Apply the Translator cognitive service for text translation

Module 4: Building Speech-Enabled Applications

A growing number of modern applications accept spoken input and respond by synthesizing speech. This module continues the exploration of natural language processing by focusing on the development of speech-enabled applications.

Lessons

• Speech Recognition and Synthesis

• Speech Translation

Lab: Recognize and Synthesize Speech

Lab: Translate Speech

Upon completing this module, learners will be able to:

• Use the Speech cognitive service for recognizing and synthesizing speech

• Use the Speech cognitive service for translating speech

Module 5: Creating Language Understanding Solutions

To build applications that intelligently understand and respond to natural language input, it is necessary to define and train a language understanding model. In this module, you will learn how to utilize the Language Understanding service to create applications that identify user intent from natural language.

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 completing this module, learners will be able to:

• Build a Language Understanding app

• Develop a client application for Language Understanding

• Integrate Language Understanding with Speech capabilities

Module 6: Building a QnA Solution

A prevalent interaction pattern between users and AI agents involves users asking questions in natural language and the agent providing intelligent responses. 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 completing this module, learners will be able to:

• Use QnA Maker to establish a knowledge base

• Integrate a QnA knowledge base into applications or bots

Module 7: Conversational AI and the Azure Bot Service

Bots form the basis of a common type of AI application where users engage in conversations with AI agents, often mimicking interactions with humans. In this module, you will examine the Microsoft Bot Framework and Azure Bot Service, which together offer a 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 completing this module, learners will be able to:

• Develop a bot using the Bot Framework SDK

• Develop a bot using Bot Framework Composer

Module 8: Getting Started with Computer Vision

Computer vision is an AI domain where software interprets visual input from images or video. In this module, you will begin exploring computer vision by learning how to use cognitive services to analyze images and video content.

Lessons

• Analyzing Images

• Analyzing Videos

Lab: Analyze Video

Lab: Analyze Images with Computer Vision

Upon completing this module, learners will be able to:

• Use the Computer Vision service to analyze images

• Use Video Analyzer to analyze video files

Module 9: Developing Custom Vision Solutions

While general computer vision capabilities are useful in many scenarios, there are instances requiring the training of custom models using specific visual data. In this module, you will explore the Custom Vision service and learn how 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 completing this module, learners 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 cognitive services can be used to identify human faces.

Lessons

• Detecting Faces with the Computer Vision Service

• Using the Face Service

Lab: Detect, Analyze, and Recognize Faces

Upon completing this module, learners 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 task, involving the extraction of text from images or documents. In this module, you will explore cognitive services that enable the detection and reading of 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 completing this module, learners will be able to:

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

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

Module 12: Creating a Knowledge Mining Solution

Many AI scenarios ultimately involve intelligently searching for information based on user queries. AI-powered knowledge mining is a critical method for building intelligent search solutions that extract insights from large digital data repositories, allowing users to find and analyze this information.

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 completing this module, learners will be able to:

• Create an intelligent search solution with Azure Cognitive Search

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

• Use Azure Cognitive Search to create a knowledge store