AI067

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)