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

Module 1: Introduction to AI on Azure

Artificial Intelligence (AI) has become central to modern applications and services. In this module, you will explore common AI capabilities that can be integrated into your apps and how these are realized within Microsoft Azure. You will also examine the 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:

• Outline the considerations for developing AI-enabled applications

• Recognize the Azure services available for AI application development

Module 2: Developing AI Apps with Cognitive Services

Cognitive Services serve as the foundational components for embedding AI capabilities into your applications. This module guides you through the process of 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 utilize cognitive services within Azure

• Manage security for cognitive services

• Monitor the performance of cognitive services

• Deploy and use cognitive services in containers

Module 3: Getting Started with Natural Language Processing

Natural Language Processing (NLP) is a subset of AI focused on deriving insights from written or spoken language. In this module, you will learn to leverage cognitive services for text analysis and translation.

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

Contemporary applications frequently accept voice input and respond with synthesized speech. This module continues the exploration of NLP capabilities by teaching you how to develop 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 for recognizing and synthesizing voice

• Apply the Speech cognitive service for voice translation

Module 5: Creating Language Understanding Solutions

Developing an application that intelligently understands and responds to natural language requires defining and training a language understanding model. In this module, you will use the Language Understanding service to build an app that identifies user intent from natural language inputs.

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:

• Build a Language Understanding application

• Develop a client application for Language Understanding

• Integrate Language Understanding with Speech services

Module 6: Building a QnA Solution

A prevalent interaction pattern between users and AI agents involves users asking questions in natural language and the AI providing intelligent responses. This module explores how the QnA Maker service facilitates the creation 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 application or bot

Module 7: Conversational AI and the Azure Bot Service

Bots underpin a growing category of AI applications where users engage in dialogue with AI agents, often mimicking human interaction. This module delves into the Microsoft Bot Framework and the Azure Bot Service, which collectively provide the 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 Bot Framework Composer

Module 8: Getting Started with Computer Vision

Computer vision is an AI domain where software interprets visual data from images or video. In this module, you will begin your journey into computer vision by learning to use cognitive services to analyze images and videos.

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 for image analysis

• Utilize Video Analyzer for video analysis

Module 9: Developing Custom Vision Solutions

While pre-defined general computer vision capabilities are useful in many scenarios, specific use cases may require training a custom model with proprietary visual data. This module examines the Custom Vision service and how to apply it to create models for image classification and object detection.

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 represent common computer vision applications. In this module, you will explore using 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 frequent computer vision task, involving the extraction of text from images or documents. This module covers cognitive services used to detect and read 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 completion of this module, students will be able to:

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

• Apply 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-driven knowledge mining is a vital approach for constructing intelligent search solutions that extract insights from large digital data repositories, enabling users to locate and analyze these 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:

• Build 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