AI & ML Workflows with Kubernetes

This course focuses on incorporating data science and AI/ML into Kubernetes development workflows. By utilizing open-source tools like Jupyter Notebooks and TensorFlow, participants will learn strategies to accelerate and automate ML workloads with Kubernetes. The course covers topics such as AI/ML people, a day in the life of a data scientist, Kubernetes, MLOps, OpenDataHub, OpenShift Data Science, and includes a demo and additional resources. The intended audience for this course includes data scientists, machine learning engineers, AI professionals, and individuals interested in deploying ML workflows with Kubernetes.