OpenShift AI Workshop Introduction
This course uses OpenShift’s AI/ML capabilities to build and deploy intelligent applications. Attendees will learn the basics of containerized AI/ML workflows, from setting up Jupyter notebooks to using frameworks like PyTorch. The training includes best practices for model deployment, scaling, monitoring, and integrating AI/ML into existing pipelines.
Who Should Attend?
- Data scientists, ML engineers, and DevOps professionals aiming to deploy AI/ML workloads on OpenShift
- Developers interested in integrating ML pipelines and model deployments into cloud-native ecosystems
- Teams evaluating container-based solutions for scalable AI/ML projects
Prerequisite Knowledge
- Foundational knowledge of containers and Kubernetes/OpenShift operations.
- Basic understanding of machine learning concepts and frameworks (PyTorch, TensorFlow, etc.)
- Proficiency in Python is helpful (for notebook-based labs and demos)
