Kubeflow Fundamentals Training Course

Kubeflow is a robust toolkit designed to simplify, portability, and scalability of Machine Learning (ML) workloads on Kubernetes.

This instructor-led live session, available both online and onsite, is tailored for developers and data scientists looking to construct, deploy, and oversee machine learning workflows within a Kubernetes environment.

Upon completing this training, participants will be equipped to:

• Install and configure Kubeflow in on-premise and cloud environments.
• Develop, deploy, and administer ML workflows leveraging Docker containers and Kubernetes.
• Execute comprehensive machine learning pipelines across various architectures and cloud platforms.
• Utilize Kubeflow to generate and manage Jupyter notebooks.
• Create ML training, hyperparameter tuning, and serving workloads across multiple platforms.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and practical drills.
• Hands-on implementation within a live-lab setting.

Customization Options

• To arrange a tailored training for this course, please reach out to us.
• For additional information on Kubeflow, visit: https://github.com/kubeflow/kubeflow