CloudThat – Training

Section 1

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.

Section 2

Lessons

1

Introduction to Artificial Intelligence

2

Artificial Intelligence in Azure

Section 3

Module 2: Developing AI Apps with Cognitive Services

1

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.

2

Using Cognitive Services for Enterprise Applications

Section 4

Lessons

1

Getting Started with Cognitive Services

2

Using Cognitive Services for Enterprise Applications

Section 5

Hands-on Lab :

1

Get Started with Cognitive Services

2

Manage Cognitive Services Security

3

Monitor Cognitive Services

4

Use a Cognitive Services Container

Section 6

Module 3: Getting Started with Natural Language Processing

1

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.

Section 7

Lessons

Section 8

Hands-on Lab :

Section 9

Module 4: Building Speech-Enabled Applications

1

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.

Section 10

Lessons

1

Speech Recognition and Synthesis

2

Speech Translation

Section 11

Hands-on Lab :

1

Recognize and Synthesize Speech

2

Translate Speech

Section 12

Module 5: Creating Language Understanding Solutions

1

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.

Section 13

Lessons

1

Creating a Language Understanding App

2

Publishing and Using a Language Understanding App

3

Using Language Understanding with Speech

Section 14

Hands-on Lab :

1

Create a Language Understanding App

2

Create a Language Understanding Client Application

3

Use the Speech and Language Understanding Services

Section 15

Module 6: Building a QnA Solution

1

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.

Section 16

Lessons

1

Creating a QnA Knowledge Base

2

Publishing and Using a QnA Knowledge Base

Section 17

Module 7: Conversational AI and the Azure Bot Service

1

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.

Section 18

Lessons

1

Bot Basics

2

Implementing a Conversational Bot

Section 19

Hands-on Lab :

1

Create a Bot with the Bot Framework SDK

2

Create a Bot with Bot Framework Composer

Section 20

Module 8: Getting Started with Computer Vision

1

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.

Section 21

Lessons

Section 22

Hands-on Lab :

1

Analyze Images with Computer Vision

2

Analyze Video with Video Indexer

Section 23

Module 9: Developing Custom Vision Solutions

1

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.

Section 24

Lessons

Section 25

Hands-on Lab :

1

Classify Images with Custom Vision

2

Detect Objects in Images with Custom Vision

Section 26

Module 10: Detecting

Section 27

Analyzing

Section 28

and Recognizing Faces

1

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.

Section 29

Lessons

1

Detecting Faces with the Computer Vision Service

2

Using the Face Service

Section 30

Hands-on Lab :

1

Detect, Analyze, and Recognize Faces

Section 31

Module 11: Reading Text in Images and Documents

1

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.

Section 32

Lessons

1

Reading text with the Computer Vision Service

2

Extracting Information from Forms with the Form Recognizer service

Section 33

Hands-on Lab :

1

Extract Data from Forms

Section 34

Module 12: Creating a Knowledge Mining Solution

1

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.

Section 35

Lessons

1

Implementing an Intelligent Search Solution

2

Developing Custom Skills for an Enrichment Pipeline

3

Creating a Knowledge Store

Section 36

Hands-on Lab :

1

Create an Azure Cognitive Search solution

2

Create a Custom Skill for Azure Cognitive Search

3

Create a Knowledge Store with Azure Cognitive Search

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

Hey there, great course, right? Do you like this course?

Course sections

Module 1: Introduction to AI on Azure

Lessons

Module 2: Developing AI Apps with Cognitive Services

Lessons

Hands-on Lab :

Module 3: Getting Started with Natural Language Processing

Lessons

Hands-on Lab :

Module 4: Building Speech-Enabled Applications

Lessons

Hands-on Lab :

Module 5: Creating Language Understanding Solutions

Lessons

Hands-on Lab :

Module 6: Building a QnA Solution

Lessons

Module 7: Conversational AI and the Azure Bot Service

Lessons

Hands-on Lab :

Module 8: Getting Started with Computer Vision

Lessons

Hands-on Lab :

Module 9: Developing Custom Vision Solutions

Lessons

Hands-on Lab :

Module 10: Detecting

Analyzing

and Recognizing Faces

Lessons

Hands-on Lab :

Module 11: Reading Text in Images and Documents

Lessons

Hands-on Lab :

Module 12: Creating a Knowledge Mining Solution

Lessons

Hands-on Lab :

Questions

Module 1: Introduction to AI on Azure

Those Other College Expenses You Aren’t Thinking About

Lesson is locked. Please Buy course to proceed.