Red Hat OpenShift AI learning 

OpenShift AI gives data scientists and developers a powerful AI/ML platform for building AI-enabled applications. Data scientists and developers can collaborate to move from experiment to production in a consistent environment quickly.

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Fundamentals of OpenShift AI
Learning Path

Introduction to OpenShift AI

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Learning Path

Demystify RAG with OpenShift AI and Elasticsearch

Understand how retrieval-augmented generation (RAG) works and how users can...
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Learning Path

From Podman AI Lab to OpenShift AI

Learn how to rapidly prototype AI applications from your local environment...
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Learning Path

Utilize Retrieval-Augmented Generation (RAG) with Node.js to optimize your AI...

We will use Langchain.js to simplify interacting with the model and will use...
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Learning Path

Deploying your LangChain.js Node.js applications to OpenShift AI

This learning exercise will deploy an existing Node.js application based on...
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Learning Path

Building and Evaluating a Fraud Detection Model with TensorFlow and ONNX

In this learning exercise, we'll focus on training and deploying your trained...
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Diving Deeper with large language models and Node.js
Learning Path

Diving Deeper with large language models and Node.js

In this learning path we dig deeper into using large language models (LLMs)...
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Learning Path

Automation ML pipeline with OpenShift AI

This learning exercise delves into the end-to-end process of building and...
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Real-time Data Collection
Learning Path

Real-time Data Collection and Processing using AI/ML on OpenShift AI

In this learning exercise, we'll explore how to set up a robust system for...
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Data Engineering
Learning Path

Data Engineering : Extract live Data Collection from images and logs

Explore the complete MLOps pipeline, utilizing OpenShift AI. The MLOps...
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Learning Path

How to get started with large language models and Node.js

Learn how to access a large language model using Node.js and LangChain.js....
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Red Hat Training and Certification courses

Looking for more? Build the skills needed to train, deploy, and serve models in Red Hat OpenShift AI, and apply best practices in machine learning and data science.

Remote container development

Develop and deploy AI/ML applications

Build the core skills for using Red Hat OpenShift AI to develop and deploy AI/ML applications, so you can train, develop, and deploy machine learning models.

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Remote container development

OpenShift AI Technical Overview (no-cost introductory offer)

Explore the current AI/ML landscape, and how Red Hat OpenShift AI builds on the capabilities of Red Hat OpenShift to provide a single, consistent, enterprise-ready hybrid AI and MLOps platform.

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Build smarter with Red Hat OpenShift AI

OpenShift AI gives data scientists and developers a powerful AI/ML platform for building AI-enabled applications. Data scientists and developers can collaborate to move from experiment to production in a consistent environment quickly.

OpenShift AI is available as an add-on cloud service to Red Hat OpenShift Service on AWS or Red Hat OpenShift Dedicated or as a self-managed software product. It provides an AI platform with popular open source tooling. Familiar tools and libraries like Jupyter, TensorFlow, and PyTorch along with MLOps components for model serving and data science pipelines are integrated into a flexible UI.

Get started with OpenShift AI