Red Hat OpenShift AI Technical Overview


An introduction to operationalizing AI/ML with Red Hat OpenShift AI

Course Description

  • This free Technical Overview describes the current AI/ML landscape and the challenges associated with developing and deploying AI/ML applications. The on-demand video content also covers 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.

Course Content Summary

  • How did AI progress to where we are today?
  • How the AI/ML landscape is evolving
  • Red Hat OpenShift AI Architecture
  • Red Hat’s AI/ML partner ecosystem
  • Use case demo

Audience for this course

  • Data scientists and AI practitioners who want to build and train ML models
  • Developers who want to build and integrate AI/ML enabled applications
  • MLOps engineers responsible for installing, configuring, deploying, and monitoring AI/ML applications

Recommended training

  • There are no prerequisites for this Technical Overview.

Technology considerations

  • N/A


Course Outline

  • Introduction
  • A brief history of AI
  • What is machine learning?
  • What is deep learning?
  • Where do foundation models fit within AI?
  • The evolving AI/ML landscape
  • The challenge with MLOps
  • Operationalizing AI
  • Red Hat OpenShift AI features
  • The Red Hat OpenShift AI open source ecosystem
  • Red Hat OpenShift AI architecture
  • The Red Hat OpenShift AI partner ecosystem
  • Demo: Improving insurance claims process
  • Demo: Connection and Setup
  • Demo: Working with an LLM
  • Demo: Image processing
  • How to continue training on Red Hat OpenShift AI


Recommended next course or exam

  • Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267)