Introduction to Machine Learning with Azure

Overview

Gain a high-level introduction to the field of machine learning and prepare to use Azure Machine Learning Studio to train machine learning models. Plus, learn how to perform a variety of tasks on Azure Machine Learning labs — from data import, transformation and management to training, validating and evaluating models. Access to the Azure Machine Learning Labs will close after a predetermined number of students have completed the course.

Syllabus

Introduction to Machine Learning

In this lesson, we'll give you a high-level introduction to the field of machine learning. In the process, you will also train your first machine learning model using Azure Machine Learning Studio.

Model Training

This lesson is about how to prepare data and then transform it into trained machine learning models. This lesson will also introduce you to ensemble learning and automated machine learning.

Supervised & Unsupervised Learning

This lesson covers two of Machine Learning's fundamental approaches: supervised and unsupervised learning. We'll learn about classification, regression, clustering, representation learning, and more.

Applications of Machine Learning

In this lesson we'll look at some of the most important applications of ML, including deep learning, similarity learning, text classification, feature learning, and anomaly detection.

Managed Services for Machine Learning

In this lesson you'll learn how to enhance your ML processes with managed services. We'll discuss computing resources, the modeling process, automation via pipelines, and more.

Responsible AI

This lesson will tackle some of the potential implications and challenges posed by ML and AI—as well as principles for building responsible AI that avoids harming others.

Course Conclusion

Congratulations on completing the course! In this short lesson, we'll recap what you've learned and talk briefly about the future of Machine Learning.