Kubeflow Fundamentals Training Course

Kubeflow serves as a comprehensive toolkit designed to simplify, port, and scale Machine Learning (ML) operations on Kubernetes.

This instructor-led, live training—available online or onsite—is tailored for developers and data scientists looking to create, deploy, and oversee machine learning workflows on Kubernetes.

Upon completion of this course, participants will be equipped to:

• Install and configure Kubeflow in both on-premise and cloud environments.
• Construct, deploy, and administer ML workflows leveraging Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud settings.
• Leverage Kubeflow to initiate and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads spanning multiple platforms.

Course Structure

• Engaging lectures and interactive discussions.
• Abundant exercises and practical application.
• Hands-on implementation within a live-lab setting.

Customization Possibilities

• Interested in a tailored training experience? Please reach out to us to make arrangements.
• For further insights into Kubeflow, visit: https://github.com/kubeflow/kubeflow