Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam Bundle

Course Description

An introduction to developing and deploying AI/ML applications on Red Hat OpenShift AI.

Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267) provides students with the fundamental knowledge about using Red Hat OpenShift for developing and deploying AI/ML applications. This course helps students build core skills for using Red Hat OpenShift AI to train, develop and deploy machine learning models through hands-on experience.

This course is based on Red Hat OpenShift® 4.14, and Red Hat OpenShift AI 2.8. The Red Hat Certified Specialist in OpenShift AI Exam (EX267) is included in the offering.

Course Content Summary

• Introduction to Red Hat OpenShift AI
• Data Science Projects
• Jupyter Notebooks
• Installing Red Hat OpenShift AI
• Managing Users and Resources
• Custom Notebook Images
• Introduction to Machine Learning
• Training Models
• Enhancing Model Training with RHOAI
• Introduction to Model Serving
• Model Serving  in Red Hat OpenShift AI
• Introduction to Workflow Automation
• Elyra Pipelines
• Kubeflow Pipelines

Target Audience

• Data scientists and AI practitioners who want to use Red Hat OpenShift AI 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 on Red Hat OpenShift AI

Recommended training

• Experience with Git is required
• Experience in Python development is required, or completion of the Python Programming with Red Hat (AD141) course
• Experience in Red Hat OpenShift is required, or completion of the Red Hat OpenShift Developer II: Building and Deploying Cloud-native Applications (DO288) course
• Basic experience in the AI, data science, and machine learning fields is recommended

Technology considerations

• No ILT classroom will be available