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

Module 1: Introduction to AI on Azure

Artificial Intelligence (AI) is becoming increasingly central to modern applications and services. During this module, you will explore common AI capabilities available for integration into your apps and how they are realized within Microsoft Azure. You will also gain insight into best practices for designing and implementing AI solutions with a focus on responsibility.

Lessons

• Introduction to Artificial Intelligence

• Artificial Intelligence in Azure

Upon completing this module, students will be able to:

• Outline key considerations for developing AI-enabled applications

• Identify specific 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 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 completing this module, students will be able to:

• Provision and consume cognitive services within Azure

• Manage security settings for cognitive services

• Monitor the performance and status 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 to apply cognitive services for the analysis and translation of text.

Lessons

• Analyzing Text

• Translating Text

Lab : Translate Text

Lab : Analyze Text

Upon completing this module, students will be able to:

• Utilize the Text Analytics cognitive service for text analysis

• Use the Translator cognitive service for text translation

Module 4: Building Speech-Enabled Applications

Many contemporary apps and services now accept spoken input and can respond through text synthesis. This module continues your exploration of natural language processing by focusing on the construction of speech-enabled applications.

Lessons

• Speech Recognition and Synthesis

• Speech Translation

Lab : Recognize and Synthesize Speech

Lab : Translate Speech

Upon completing this module, students will be able to:

• Employ the Speech cognitive service for recognizing and synthesizing speech

• Use the Speech cognitive service to translate spoken language

Module 5: Creating Language Understanding Solutions

To build an application capable of intelligently understanding and responding to natural language input, it is necessary to define and train a language understanding model. In this module, you will learn to use the Language Understanding service to create an app that identifies 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 completing this module, students will be able to:

• Develop a Language Understanding app

• Build a client application for Language Understanding

• Integrate Language Understanding with Speech services

Module 6: Building a QnA Solution

A prevalent interaction model between users and AI agents involves users posing questions in natural language and the AI agent providing intelligent, appropriate answers. 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, students will be able to:

• Use QnA Maker to establish a knowledge base

• Implement a QnA knowledge base within an application or bot

Module 7: Conversational AI and the Azure Bot Service

Bots represent a growing category of AI applications where users engage in conversations with AI agents, often mimicking interactions with human agents. In this module, you will examine the Microsoft Bot Framework and the 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, students will be able to:

• Use the Bot Framework SDK to create a bot

• Utilize the Bot Framework Composer to create a bot

Module 8: Getting Started with Computer Vision

Computer vision is an area of artificial intelligence where software applications interpret visual data from images or video. In this module, you will begin your exploration of computer vision by learning how to use cognitive services to analyze image and video content.

Lessons

• Analyzing Images

• Analyzing Videos

Lab : Analyze Video

Lab : Analyze Images with Computer Vision

Upon completing this module, students will be able to:

• Apply the Computer Vision service to analyze images

• Use 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 requiring the training of a custom model using specific visual data. In this module, you will explore the Custom Vision service and learn how to use it to build 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, 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 common scenarios in computer vision. In this module, you will explore the use of 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 completing 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 frequent computer vision scenario, wherein software extracts text from images or documents. In this module, you will explore cognitive services capable of detecting and reading text within 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, students will be able to:

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

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

Module 12: Creating a Knowledge Mining Solution

Ultimately, many AI scenarios require intelligently searching for information based on user queries. AI-driven knowledge mining is an increasingly vital method for building intelligent search solutions that leverage AI to extract insights from large digital data repositories, enabling users to discover 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 completing this module, students will be able to:

• Build an intelligent search solution using Azure Cognitive Search

• Implement custom skills within an Azure Cognitive Search enrichment pipeline

• Use Azure Cognitive Search to establish a knowledge store