Microsoft Azure Machine Learning

This course is part of multiple programs.

Instructor: Microsoft

What you'll learn

How to describe capabilities of no-code machine learning with Azure Machine Learning Studio
How to identify core tasks in creating a machine learning solution
How to describe core machine learning concepts
How to identify common machine learning types

Skills you'll gain

Details to know

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Assessments

2 quizzes, 10 assignments

Taught in English

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There are 4 modules in this course

Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code.

This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals. This is the second course in a five-course program that prepares you to take the AI-900 certification exam. This course teaches you the core concepts and skills that are assessed in the AI fundamentals exam domains. This beginner course is suitable for IT personnel who are just beginning to work with Microsoft Azure and want to learn about Microsoft Azure offerings and get hands-on experience with the product. Microsoft Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Microsoft Azure Data Scientist Associate or Microsoft Azure AI Engineer Associate, but it is not a prerequisite for any of them. This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including concepts of machine learning and artificial intelligence.

Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this module, you'll learn how to identify different kinds of machine learning model and how to use the automated machine learning capability of Azure Machine Learning to train and deploy a predictive model.

What's included

3 videos8 readings1 quiz2 assignments1 discussion prompt1 plugin

3 videosTotal 4 minutes

Introduction to Create No-code Predictive Models with Azure Machine Learning1 minutePreview module
Azure Machine Learning to Train and Deploy a Predictive Model2 minutes
Weekly Summary0 minutes

8 readingsTotal 95 minutes

Course Syllabus10 minutes
How to be successful in this course5 minutes
Exercise Part 1: Create a Microsoft Azure Machine Learning Workspace 10 minutes
Exercise Part 2: Create Compute Resources10 minutes
Exercise Part 3: Explore Data10 minutes
Exercise Part 4: Train a Machine Learning Model25 minutes
Exercise Part 5: Deploy a Model as a Service 15 minutes
Exercise Part 6: Clean-up10 minutes

1 quizTotal 15 minutes

Knowledge Check15 minutes

2 assignmentsTotal 51 minutes

Test Prep21 minutes
Exercise Quiz30 minutes

1 discussion promptTotal 10 minutes

How Does Machine Learning Influence Your Day-to-Day Life?10 minutes

1 pluginTotal 15 minutes

Azure Machine Learning15 minutes

Regression is a supervised machine learning technique used to predict numeric values. in this module, you will learn how to create regression models using Azure Machine Learning designer.

What's included

2 videos8 readings1 quiz2 assignments

2 videosTotal 2 minutes

What is Regression?1 minutePreview module
Weekly Summary0 minutes

8 readingsTotal 84 minutes

Exercise Part 1: Create a Microsoft Azure Machine Learning Workspace1 minute
Exercise Part 2: Create Compute Resources10 minutes
Exercise Part 3: Explore Data15 minutes
Exercise Part 4: Create and Run a Training Pipeline 18 minutes
Exercise Part 5: Evaluate a Regression Model 10 minutes
Exercise Part 6: Create an Inference Pipeline 12 minutes
Exercise Part 7: Deploy a Predictive Service8 minutes
Exercise Part 8: Clean-up 10 minutes

1 quizTotal 21 minutes

Test Prep21 minutes

2 assignmentsTotal 45 minutes

Exercise Quiz30 minutes
Knowledge Check15 minutes

Classification is a supervised machine learning technique used to predict categories or classes. In this module, you will learn how to create classification models using Azure Machine Learning designer.

What's included

2 videos8 readings3 assignments

2 videosTotal 2 minutes

What is Classification?1 minutePreview module
Weekly Summary0 minutes

8 readingsTotal 100 minutes

Exercise Part 1: Create an Azure Machine Learning Workspace10 minutes
Exercise Part 2: Create Compute Resources10 minutes
Exercise Part 3: Explore Data15 minutes
Exercise Part 4: Create and Run a Training Pipeline18 minutes
Exercise Part 5: Evaluate a Classification Model15 minutes
Exercise Part 6: Create an Inference Pipeline12 minutes
Exercise Part 7: Deploy a predictive service10 minutes
Exercise Part 8: Clean-up10 minutes

3 assignmentsTotal 66 minutes

Test Prep21 minutes
Exercise Quiz30 minutes
Knowledge Check15 minutes

Clustering is an unsupervised machine learning technique used to group similar entities based on their features. In this module, you will learn how to create clustering models using Azure Machine Learning designer.