IL - AI-102: Designing and Implementing a Microsoft Azure AI Solution

Course Overview

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.

Course Details
  • Duration: 4 days
  • Level: 300

Who this course is designed for
  • Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

  • Describe considerations for AI-enabled application development
  • Create, configure, deploy, and secure Azure Cognitive Services
  • Develop applications that analyze text
  • Develop speech-enabled applications
  • Create applications with natural language understanding capabilities
  • Create QnA applications
  • Create conversational solutions with bots
  • Use computer vision services to analyze images and videos
  • Create custom computer vision models
  • Develop applications that detect, analyze, and recognize faces
  • Develop applications that read and process text in images and documents
  • Create intelligent search solutions for knowledge mining
  • Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

Course Agenda

Module 1: Introduction to AI on Azure
Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.

Lessons
Introduction to Artificial Intelligence

Artificial Intelligence in Azure

After completing this module, students will be able to:

Describe considerations for creating AI-enabled applications

Identify Azure services for AI application development

Module 2: Developing AI Apps with Cognitive Services
Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy 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
After completing this module, students will be able to:

Provision and consume cognitive services in Azure

Manage cognitive services security

Monitor cognitive services

Use a cognitive services container

Module 3: Getting Started with Natural Language Processing
Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.

Lessons
Analyzing Text

Translating Text

Lab : Translate Text
Lab : Analyze Text
After completing this module, students will be able to:

Use the Text Analytics cognitive service to analyze text

Use the Translator cognitive service to translate text

Module 4: Building Speech-Enabled Applications
Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.

Lessons
Speech Recognition and Synthesis

Speech Translation

Lab : Recognize and Synthesize Speech
Lab : Translate Speech
After completing this module, students will be able to:

Use the Speech cognitive service to recognize and synthesize speech

Use the Speech cognitive service to translate speech

Module 5: Creating Language Understanding Solutions
To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use 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
After completing this module, students will be able to:

Create a Language Understanding app

Create a client application for Language Understanding

Integrate Language Understanding and Speech

Module 6: Building a QnA Solution
One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.

Lessons
Creating a QnA Knowledge Base

Publishing and Using a QnA Knowledge Base

Lab : Create a QnA Solution
After completing this module, students will be able to:

Use QnA Maker to create a knowledge base

Use a QnA knowledge base in an app or bot

Module 7: Conversational AI and the Azure Bot Service
Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide 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
After completing this module, students will be able to:

Use the Bot Framework SDK to create a bot

Use the Bot Framework Composer to create a bot

Module 8: Getting Started with Computer Vision
Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of 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
After completing this module, students will be able to:

Use the Computer Vision service to analyze images

Use Video Analyzer to analyze videos

Module 9: Developing Custom Vision Solutions
While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and 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
After completing this module, students will be able to:

Use the Custom Vision service to implement image classification

Use the Custom Vision service to implement object detection

Module 10: Detecting, Analyzing, and Recognizing Faces
Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user 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
After completing this module, students will be able to:

Detect faces with the Computer Vision service

Detect, analyze, and recognize faces with the Face service

Module 11: Reading Text in Images and Documents
Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read 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
After completing this module, students 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
Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable 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
After completing this module, students 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. 

Training Options


Dedicated Delivery

This course can be delivered dedicated to your team either virtually or onsite. A dedicated delivery allows deeper discussion with your team and our instructor on projects and workloads that are specific to your environment.

Customized Delivery

This course can be customized by adding or removing topics, going deeper on specific topics, or by customizing the delivery schedule to make it easier for your team to attend the training.

Contact a Cloud Training Specialist

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Course Schedule