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Microsoft

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

  • Duration: 4 days
  • Job Role: AI Engineer
  • Exam: AI-102

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

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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.

Audience Profile

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.

Prerequisites

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal.
  • Knowledge of either C# or Python.
  • Familiarity with JSON and REST programming semantics.

Course outline

Module 1: Introduction to AI on Azure

Module Overview

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

Lab Sessions

Not available for this module

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Get Started with Cognitive Services
Manage Cognitive Services Security
Monitor Cognitive Services
Use a Cognitive Services Container

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Analyze Text
Translate Text

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Recognize and Synthesize Speech
Translate Speech

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Create a Language Understanding App
Create a Language Understanding Client Application
Use the Speech and Language Understanding Services

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Create a QnA Solution

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Create a Bot with the Bot Framework SDK
Create a Bot with Bot Framework Composer

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Analyze Images with Computer Vision
Analyze Video with Video Indexer

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Use the Computer Vision service to analyze images.
Use Video Indexer to analyze videos.

Module 9: Developing Custom Vision Solutions

Module Overview

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 Sessions

Classify Images with Custom Vision
Detect Objects in Images with Custom Vision

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Detect, Analyze, and Recognize Faces

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Read Text in Images
Extract Data from Forms

Lab Lessons

Lab lessons not available

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

Module Overview

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 Sessions

Create an Azure Cognitive Search solution
Create a Custom Skill for Azure Cognitive Search
Create a Knowledge Store with Azure Cognitive Search

Lab Lessons

Lab lessons not available

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.

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