The Ray Data learning path provides a comprehensive guide to distributed data processing and batch inference with Ray Data. You'll learn foundational concepts, practical data processing workflows, and how to scale batch inference pipelines for production workloads.
The Ray Train learning path is a deep dive into distributed model training with Ray Train and gives you a large sample of interesting workloads to explore.
The Ray 101 learning path is the perfect entry point to get you started with Ray. You'll learn about all of our libraries, from low-level distributed computing with Ray Core to running AI workloads with Ray Data, Train, Tune and Serve
An example of distributed model training using Ray Train.
A time series data workload example built with Ray Train.
A tabular data workload example built with Ray Train.
A recommender systems workload example built with Ray Train.
A policy learning workload example utilizing Ray Train.
A generative computer vision workload example built with Ray Train.
An example of online model serving implemented with Ray Serve.
An example of distributed model training using Ray Train.
An example of data processing using Ray Data.
An example of batch inference implemented with Ray Data.
A workload example demonstrating model training with PyTorch and Lightning.
This foundation course helps you get started with running your own hyperparameter tuning experiments efficiently using Ray Tune.
Learn the foundations of distributed training of machine learning models with Ray Train.
Learn to deploy your machine learning models in this foundations course on Ray Serve.
Course by Max Pumperla
Explore the foundations of processing structured and unstructured data with Ray Data and get an overview of the key concepts and patterns for distributed data processing.
Master the basics of distributed computing with this foundations course on Ray Core.
This course is designed for users new to Ray. It serves as an introductory step in learning Ray, covering fundamentals of the Ray ecosystem and its AI libraries.
Explore the basics of observability with Ray and Anyscale in this foundations course.
Learn the end-to-end multi-modal AI pipeline, including how each component fits together and what the project provides. You’ll also gain hands-on experience running and exploring the implementation using Anyscale or the GitHub repository.
Course by Max Pumperla
Learn the fundamentals of deploying LLMs with Ray.
This course helps developers kick-start their work on Anyscale.
This course helps admins deploy Anyscale clouds in custom environments (AWS vs. GCP, VMs vs. Kubernetes, etc.).
Course by Max Pumperla
Course by Max Pumperla • February 20, 2026
Test description
Capstone certificate exam for Ray Train Specialization.
Capstone certificate exam for Ray Data Specialization.
Capstone certificate exam for Introduction to Ray.