Red Hat OpenShift Data Science
A cloud service that gives data scientists and developers a powerful AI/ML platform for building intelligent applications.
Get started with step-by-step learning paths
Learning path 1: Launch Red Hat OpenShift Data Science
In this learning path, we use a pre-existing Jupyter Notebook project to start exploring data science. Project Jupyter offers the interactive JupyterHub and JupyterLab tools, which we'll introduce in this path.
Learning path 2: Red Hat OpenShift Data Science resources
The Red hat OpenShift Data Science platform offers a number of documents and learning materials explaining how to use Red Hat managed services as well as managed services and software offered by our partners. Learning materials include how-to resources, tutorials, and quick starts.
Learning path 3: How to access, download, and analyze data for S3
In this learning path, you will start your Jupyter notebook server and select preferences for S3 usage. You will also learn how to access and download the data you create as well as analyze it, using a variety of skills and tools.
Learning path 4: How to create a TensorFlow model
In this learning path, you will set up options for your Jupyter notebook server, then explore the MNIST dataset to refine your data. Finally, you will learn how to implement frameworks, layers, and nodes to create your TensorFlow model.
Developer sandbox use-case activity
Master NLP using Red Hat OpenShift Data Science
In this tutorial, you are an intern for a city transportation department. You have been given the job to process potential bus repair issues that the drivers have noticed during their shifts. In order to keep the repair issues organized and visible, you will need to learn how to categorize them.
And all of this without having to install anything on your computer, thanks to Red Hat OpenShift Data Science!
