Kubeflow Fundamentals Training Course

Kubeflow serves as a comprehensive toolkit designed to simplify Machine Learning (ML) on Kubernetes, ensuring it remains portable and scalable.

This live, instructor-led programme—available either online or on-site—is tailored for developers and data scientists seeking to construct, deploy, and oversee machine learning workflows within a Kubernetes environment.

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

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

Course Format

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

Customisation Options

• To arrange a tailored training experience for this course, please reach out to us to discuss your requirements.
• For further details on Kubeflow, please visit: https://github.com/kubeflow/kubeflow