Getting Started with Amazon Personalize
AWS Skill Builder
Last updated October 1, 2025
Getting Started with Amazon Personalize is a free, one-hour introduction to Amazon Personalize, AWS's machine learning service for building individualized recommendations — the "customers also bought" and "suggested for you" kind of personalization. It puts the same recommendation technology Amazon.com uses within reach of an ordinary application, and is built so you can use it without deep machine learning expertise of your own: you supply data about your users and what they interact with, and the service learns to suggest what each user is likely to want next. The course covers the service essentials — how Personalize works, its technical overview, and how to put it to use — and includes a demonstration so you can see what building recommendations with it actually involves.
What you'll learn
- What Personalize is and how it generates individualized recommendations
- How a managed service delivers personalization without deep ML expertise
- The technical concepts behind it
- Using it to build scalable, reliable solutions
- A guided demonstration
Frequently asked questions about Getting Started with Amazon Personalize
Who is Getting Started with Amazon Personalize for?
Beginners — particularly developers — who want a hands-on first look at adding individualized recommendations to an application with a managed machine learning service, using Amazon Personalize.
Is Getting Started with Amazon Personalize free?
Yes — Getting Started with Amazon Personalize is completely free to take.
What are the prerequisites for Getting Started with Amazon Personalize?
AWS Cloud Technical Essentials recommended; an AWS account is needed for the demonstration.
Why we suggest this course
A short, concrete first look at how a managed machine learning service produces individualized recommendations — the personalization behind a tailored feed or product suggestion — without requiring you to build the models yourself, paired with a demonstration rather than theory alone. One thing to know: this is an introduction to a single AWS service, so it is vendor-specific by design rather than a general tour of recommender systems — what you learn applies to Amazon Personalize in particular, though the underlying idea of learning from user behavior to suggest what comes next is common across recommendation tools.