Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267) Course Overview
The 'Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267)' course equips professionals, including developers, data scientists, and DevOps engineers, with essential skills to build and manage AI/ML applications on OpenShift. This course is crucial for leveraging AI capabilities effectively, enabling organizations to enhance innovation and scalability in their projects.
Course outline & what you'll learn
Overview of OpenShift and its components
- Understanding AI/ML concepts and workflows
- Installation and configuration of OpenShift
- Tools and resources for AI/ML development
- Data collection and preprocessing
- Data storage and access in OpenShift
- Introduction to popular ML frameworks (e.g., TensorFlow, PyTorch)
- Model development and training processes
- Techniques for deploying models on OpenShift
- Scaling and managing AI/ML applications
- Strategies for monitoring AI/ML performance
- Updating and maintaining deployed applications
- Understanding security best practices
- Compliance considerations for AI/ML applications
- Review of successful AI/ML deployments
- Lessons learned from industry implementations
- Hands-on project to apply course concepts
- Evaluation and feedback on project implementation
Why train with Traincrest
This Red Hat course is delivered by Traincrest's certified instructors, live online or in the classroom, with hands-on labs and a 98% exam success rate. Trusted by 500+ companies and 50,000+ students worldwide.