Fundamentals of Machine Learning on AWS

by Amber Israelsen

Machine learning is one of the hottest fields in the world today. This course will teach you how to get started solving business problems with AWS machine learning technologies.

What you'll learn

You’ve probably heard about how machine learning is shaping our world--from facial recognition to package delivery, speech recognition to self-driving cars. But how do you get started in this exciting field?

In this course, Fundamentals of Machine Learning on AWS, you’ll learn how to solve business problems with AWS machine learning technologies. First, you’ll explore what ML is and how it relates to artificial intelligence and deep learning. Next, you’ll learn how to identify and frame opportunities for machine learning. Then, you’ll discover the end-to-end machine learning process: fetching, cleaning and preparing data, training and evaluating models, and deploying and monitoring models. Finally, you’ll learn the AWS artificial intelligence and machine learning technologies that enable this process, and see them in action with Amazon SageMaker Studio.

When you’re finished with this course, you’ll have the skills and knowledge of AWS machine learning technologies needed to solve real-world problems. This course will also lay the foundation for the AWS Machine Learning Specialty certification.

Table of contents

Course Overview

About the author

Amber has been a software developer and technical trainer since the early 2000s. She holds certifications for AWS and a variety of Microsoft technologies. In recent years, she has focused on AWS, Machine Learning, Azure, Power Apps, Dynamics 365, SharePoint and .NET, teaching students around the world. She also works to bridge the gap between developers, designers and businesspeople with her expertise in visual communication, user experience and business/professional skills.

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