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Creating a AI and Machine Learning course using Microsoft Learn

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Lee_Stott
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May 26, 2020

Defining Modules for AI and Machine Learning 

I wanted to share some guidance on using Microsoft Learn resources to build a rounded curriculum and insights into the specific modules and assessments for AI and Machine Learning courses.  From this content your course should have some great graduate outcomes. 


Module 1. Introduction to AI

Get Started with AI Fundamentals



Module 2. Machine learning 

Create no-code predictive models with Azure Machine Learning

Academic Capstone Project - Build an Machine Learning Model

Module 3. Computer Vision 

Explore Computer Vision in Microsoft Azure

Academic Capstone Project - Build a Computer Vision Solution

 

Module 4. Natural Language Processing 

Explore Natural Language Processing

Academic Capstone Project - Build a Natural Language Processing Solution 


Module 5. Conversational AI

Explore Conversational AI

Academic Capstone Project - Build a Bot

Example course structure and resources 

Module and Description

Lesson

Key Topics

In-Class Demonstrations and Labs

Aligned Online Learning on Microsoft Learn

Module 0 – Course Introduction:

This module provides a high-level course format and objectives as well as an outline of the course.

 

 

 

 

Module 1 – Introduction to AI:

In this module, you'll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You'll then explore considerations and principles for responsible AI development.

Lesson 1 – Azure AI Fundamentals

What is Artificial Intelligence?

Common Artificial Intelligence Workloads

Artificial Intelligence in Microsoft Azure

What can you do with Artificial Intelligence?

Demo: Getting started with the Azure portal  

Get Started with Azure AI Fundamentals

Lesson 2 – Responsible AI

Challenges and Risks with AI

Principles of Responsible AI

Lab: Review example scenarios and identify the Responsible AI principle(s) that apply

Module 2 – Machine Learning:

Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

Lesson 1 –Introduction to Machine Learning

What is machine learning?

Regression

Classification

Clustering

 

Create no-code predictive models with Azure Machine Learning

Lesson 2 – Azure Machine Learning

What is Azure Machine Learning?

Automated machine learning

Azure Machine Learning Designer

Lab: Create an Azure Machine Learning workspace, create compute targets, explore data, train a machine learning model, and deploy a model as a service

Optional Demonstration: Create a classification model with Azure Machine Learning Designer

Module 3 – Computer Vision:

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services

Lesson 1 – Computer Vision Concepts

What is Computer Vision

Computer Vision Models

Applications of Computer Vision

Demo: Show some examples of Computer Vision

Explore Computer Vision in Microsoft Azure

Lesson 2 – Computer Vision in Azure

Cognitive Services

Image Analysis with the Computer Vision Service

Training Models with the Custom Vision Service

Analyzing Faces with the Face Service

Reading Text with the Computer Vision Service

Analyzing Forms with the Form Recognizer Service

Lab: Create an image classification solution

Module 4 – Natural Language Processing:

This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands

Lesson 1 – Introduction to Natural Language Processing

What is Natural Language Processing?

Natural Language Processing in Azure

Demo: Natural Language Processing

Explore Natural Language Processing

Lesson 2 – Using Natural Language Processing Services

Text Analytics

Speech Recognition and Synthesis

Translation

Language Understanding

Lab: Create a LUIS application

Module 5 – Conversational AI:

Conversational AI enables users to engage in a dialog with an AI agent, or Bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions.

Lesson 1 – Conversational AI Concepts

What is Conversational AI?

Responsible AI Guidelines for Bots

Demo: Using a Bot

Explore Conversational AI

Lesson 2 – Conversational AI in Azure

QnA Maker Service

Azure Bot Service

Lab: Create a Bot

Updated Jun 16, 2020
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Providing industrial and international perspective for instructor lead teaching and blended learning using Microsoft Learn.

","body":"

Defining Modules for AI and Machine Learning 

\n

I wanted to share some guidance on using Microsoft Learn resources to build a rounded curriculum and insights into the specific modules and assessments for AI and Machine Learning courses.  From this content your course should have some great graduate outcomes. 

\n


Module 1. Introduction to AI

\n

Get Started with AI Fundamentals

\n



Module 2. Machine learning 

\n

Create no-code predictive models with Azure Machine Learning

\n

Academic Capstone Project - Build an Machine Learning Model

\n

Module 3. Computer Vision 

\n

Explore Computer Vision in Microsoft Azure

\n

Academic Capstone Project - Build a Computer Vision Solution

\n

 

\n

Module 4. Natural Language Processing 

\n

Explore Natural Language Processing

\n

\n

Academic Capstone Project - Build a Natural Language Processing Solution 


Module 5. Conversational AI

\n

Explore Conversational AI

\n

\n

Academic Capstone Project - Build a Bot

\n

Example course structure and resources 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Module and Description

\n
\n

Lesson

\n
\n

Key Topics

\n
\n

In-Class Demonstrations and Labs

\n
\n

Aligned Online Learning on Microsoft Learn

\n
\n

Module 0 – Course Introduction:

\n

This module provides a high-level course format and objectives as well as an outline of the course.

\n
\n

 

\n
\n

 

\n
\n

 

\n
\n

 

\n
\n

Module 1 – Introduction to AI:

\n

In this module, you'll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You'll then explore considerations and principles for responsible AI development.

\n
\n

Lesson 1 – Azure AI Fundamentals

\n
\n

What is Artificial Intelligence?

\n

Common Artificial Intelligence Workloads

\n

Artificial Intelligence in Microsoft Azure

\n

What can you do with Artificial Intelligence?

\n
\n

Demo: Getting started with the Azure portal  

\n
\n

Get Started with Azure AI Fundamentals

\n
\n

Lesson 2 – Responsible AI

\n
\n

Challenges and Risks with AI

\n

Principles of Responsible AI

\n
\n

Lab: Review example scenarios and identify the Responsible AI principle(s) that apply

\n
\n

Module 2 – Machine Learning:

\n

Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

\n
\n

Lesson 1 –Introduction to Machine Learning

\n
\n

What is machine learning?

\n

Regression

\n

Classification

\n

Clustering

\n
\n

 

\n
\n

Create no-code predictive models with Azure Machine Learning

\n
\n

Lesson 2 – Azure Machine Learning

\n
\n

What is Azure Machine Learning?

\n

Automated machine learning

\n

Azure Machine Learning Designer

\n
\n

Lab: Create an Azure Machine Learning workspace, create compute targets, explore data, train a machine learning model, and deploy a model as a service

\n

Optional Demonstration: Create a classification model with Azure Machine Learning Designer

\n
\n

Module 3 – Computer Vision:

\n

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services

\n
\n

Lesson 1 – Computer Vision Concepts

\n
\n

What is Computer Vision

\n

Computer Vision Models

\n

Applications of Computer Vision

\n
\n

Demo: Show some examples of Computer Vision

\n
\n

Explore Computer Vision in Microsoft Azure

\n
\n

Lesson 2 – Computer Vision in Azure

\n
\n

Cognitive Services

\n

Image Analysis with the Computer Vision Service

\n

Training Models with the Custom Vision Service

\n

Analyzing Faces with the Face Service

\n

Reading Text with the Computer Vision Service

\n

Analyzing Forms with the Form Recognizer Service

\n
\n

Lab: Create an image classification solution

\n
\n

Module 4 – Natural Language Processing:

\n

This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands

\n
\n

Lesson 1 – Introduction to Natural Language Processing

\n
\n

What is Natural Language Processing?

\n

Natural Language Processing in Azure

\n
\n

Demo: Natural Language Processing

\n
\n

Explore Natural Language Processing

\n
\n

Lesson 2 – Using Natural Language Processing Services

\n
\n

Text Analytics

\n

Speech Recognition and Synthesis

\n

Translation

\n

Language Understanding

\n
\n

Lab: Create a LUIS application

\n
\n

Module 5 – Conversational AI:

\n

Conversational AI enables users to engage in a dialog with an AI agent, or Bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions.

\n
\n

Lesson 1 – Conversational AI Concepts

\n
\n

What is Conversational AI?

\n

Responsible AI Guidelines for Bots

\n
\n

Demo: Using a Bot

\n
\n

Explore Conversational AI

\n
\n

Lesson 2 – Conversational AI in Azure

\n
\n

QnA Maker Service

\n

Azure Bot Service

\n
\n

Lab: Create a Bot

\n
","body@stringLength":"12339","rawBody":"

Defining Modules for AI and Machine Learning 

\n

I wanted to share some guidance on using Microsoft Learn resources to build a rounded curriculum and insights into the specific modules and assessments for AI and Machine Learning courses.  From this content your course should have some great graduate outcomes. 

\n


Module 1. Introduction to AI

\n

Get Started with AI Fundamentals

\n



Module 2. Machine learning 

\n

Create no-code predictive models with Azure Machine Learning

\n

Academic Capstone Project - Build an Machine Learning Model

\n

Module 3. Computer Vision 

\n

Explore Computer Vision in Microsoft Azure

\n

Academic Capstone Project - Build a Computer Vision Solution

\n

 

\n

Module 4. Natural Language Processing 

\n

Explore Natural Language Processing

\n

\n

Academic Capstone Project - Build a Natural Language Processing Solution 


Module 5. Conversational AI

\n

Explore Conversational AI

\n

\n

Academic Capstone Project - Build a Bot

\n

Example course structure and resources 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Module and Description

\n
\n

Lesson

\n
\n

Key Topics

\n
\n

In-Class Demonstrations and Labs

\n
\n

Aligned Online Learning on Microsoft Learn

\n
\n

Module 0 – Course Introduction:

\n

This module provides a high-level course format and objectives as well as an outline of the course.

\n
\n

 

\n
\n

 

\n
\n

 

\n
\n

 

\n
\n

Module 1 – Introduction to AI:

\n

In this module, you'll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You'll then explore considerations and principles for responsible AI development.

\n
\n

Lesson 1 – Azure AI Fundamentals

\n
\n

What is Artificial Intelligence?

\n

Common Artificial Intelligence Workloads

\n

Artificial Intelligence in Microsoft Azure

\n

What can you do with Artificial Intelligence?

\n
\n

Demo: Getting started with the Azure portal  

\n
\n

Get Started with Azure AI Fundamentals

\n
\n

Lesson 2 – Responsible AI

\n
\n

Challenges and Risks with AI

\n

Principles of Responsible AI

\n
\n

Lab: Review example scenarios and identify the Responsible AI principle(s) that apply

\n
\n

Module 2 – Machine Learning:

\n

Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

\n
\n

Lesson 1 –Introduction to Machine Learning

\n
\n

What is machine learning?

\n

Regression

\n

Classification

\n

Clustering

\n
\n

 

\n
\n

Create no-code predictive models with Azure Machine Learning

\n
\n

Lesson 2 – Azure Machine Learning

\n
\n

What is Azure Machine Learning?

\n

Automated machine learning

\n

Azure Machine Learning Designer

\n
\n

Lab: Create an Azure Machine Learning workspace, create compute targets, explore data, train a machine learning model, and deploy a model as a service

\n

Optional Demonstration: Create a classification model with Azure Machine Learning Designer

\n
\n

Module 3 – Computer Vision:

\n

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services

\n
\n

Lesson 1 – Computer Vision Concepts

\n
\n

What is Computer Vision

\n

Computer Vision Models

\n

Applications of Computer Vision

\n
\n

Demo: Show some examples of Computer Vision

\n
\n

Explore Computer Vision in Microsoft Azure

\n
\n

Lesson 2 – Computer Vision in Azure

\n
\n

Cognitive Services

\n

Image Analysis with the Computer Vision Service

\n

Training Models with the Custom Vision Service

\n

Analyzing Faces with the Face Service

\n

Reading Text with the Computer Vision Service

\n

Analyzing Forms with the Form Recognizer Service

\n
\n

Lab: Create an image classification solution

\n
\n

Module 4 – Natural Language Processing:

\n

This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands

\n
\n

Lesson 1 – Introduction to Natural Language Processing

\n
\n

What is Natural Language Processing?

\n

Natural Language Processing in Azure

\n
\n

Demo: Natural Language Processing

\n
\n

Explore Natural Language Processing

\n
\n

Lesson 2 – Using Natural Language Processing Services

\n
\n

Text Analytics

\n

Speech Recognition and Synthesis

\n

Translation

\n

Language Understanding

\n
\n

Lab: Create a LUIS application

\n
\n

Module 5 – Conversational AI:

\n

Conversational AI enables users to engage in a dialog with an AI agent, or Bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions.

\n
\n

Lesson 1 – Conversational AI Concepts

\n
\n

What is Conversational AI?

\n

Responsible AI Guidelines for Bots

\n
\n

Demo: Using a Bot

\n
\n

Explore Conversational AI

\n
\n

Lesson 2 – Conversational AI in Azure

\n
\n

QnA Maker Service

\n

Azure Bot Service

\n
\n

Lab: Create a Bot

\n
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Providing industrial and international perspective for instructor lead teaching and blended learning using Microsoft Learn.

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