Amazon SageMaker AI Getting Started
AWS Skill Builder
Last updated September 15, 2025
Amazon SageMaker AI Getting Started is a free, one-hour introduction to Amazon SageMaker AI, AWS's managed machine learning service. The real substance is hands-on: in a guided demonstration you create a SageMaker AI notebook instance, then open a Jupyter notebook and run sample code that trains a machine learning model and uses it to generate predictions — the full train-then-predict loop in miniature. Around that, the course covers the benefits and technical concepts of the service, the kinds of problems it is built to solve, and how its pricing works. You run Python in a notebook, so some comfort with the language helps.
What you'll learn
- Purpose, benefits, technical concepts of SageMaker AI
- The kinds of problems it solves
- How pricing is structured
- Creating a notebook instance
- Running sample code in a Jupyter notebook to train a model
- Using the model to generate predictions
Frequently asked questions about Amazon SageMaker AI Getting Started
Who is Amazon SageMaker AI Getting Started for?
Beginners with some Python who want a hands-on first taste of training and serving a machine learning model on Amazon SageMaker AI.
Is Amazon SageMaker AI Getting Started free?
Yes — Amazon SageMaker AI Getting Started is completely free to take.
What are the prerequisites for Amazon SageMaker AI Getting Started?
Basic Python proficiency and AWS Technical Essentials recommended; an AWS account is needed to run the hands-on notebook.
Do you need to code for Amazon SageMaker AI Getting Started?
Yes — Amazon SageMaker AI Getting Started involves hands-on coding.
Why we suggest this course
It leads with the part that transfers: a guided, hands-on session where you spin up a notebook, train a model, and generate predictions — the core train-then-predict workflow — rather than only touring the service. One thing to know: this is an introduction to a single AWS service, so the framing is vendor-specific by design and part of the course covers SageMaker's purpose and pricing; the machine learning workflow you practice, though, is a general skill.