Create and configure production-grade ROSA clusters as part of a larger AWS customer’s footprint.
Creating and Configuring Production ROSA Clusters (CS220) teaches how to configure ROSA clusters as part of pre-existing AWS environments and how to integrate ROSA with AWS services commonly used by IT operations teams, such as Amazon CloudWatch.
Address security challenges by applying Red Hat Advanced Cluster Security for Kubernetes in an OpenShift cluster environment.
Customers want to learn how Red Hat Advanced Cluster Security for Kubernetes (RHACS) can help them solve their security challenges. However, their security teams might lack experience with Kubernetes and OpenShift, and so they have challenges with implementation. In particular, their security teams have several needs:
RHACS customers might already be using external image registries and Security Information and Event Management (SIEM) tools. They need to integrate RHACS with their existing set of external components to achieve their security goals.
Introduction to concepts and fundamental skills for Linux users who run applications and services in Linux environments, but do not perform Linux system administration.
Getting Started with Linux Fundamentals (RH104) is designed for IT professionals and business users who access Linux systems, and run Linux-based applications and services, but have little to no previous UNIX or Linux experience. This course introduces Linux concepts and fundamental skills to Linux users who do not manage or administer Linux systems. Professionals who require system administration skills should instead take Red Hat System Administration I (RH124).
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 ® 4.16, and Red Hat OpenShift AI 2.13.
Experience the possibilities of MLOps through proven open culture and practices used by Red Hat to support customer innovation.
MLOps Practices with Red Hat OpenShift AI (AI500) is a five-day immersive class that guides attendees through a complete MLOps adoption journey. Unlike trainings focused on a single framework or tool, it demonstrates how leading open-source technologies integrate into a full MLOps workflow, blending continuous discovery, training, and delivery in realistic machine learning scenarios.
Cross-functional participation is essential for achieving the learning goals. Data scientists, ML engineers, platform engineers, architects, and product owners collaborate in a simulated real-world delivery environment. This daily routine shows how breaking down silos and working as a unified team drives innovation, equips participants with shared best practices, and strengthens organizational culture and processes.
The course is built on Red Hat technologies, specifically Red Hat OpenShift AI, Red Hat OpenShift GitOps, and Predictive AI, providing a practical foundation for applying modern MLOps methodologies.
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