Kubeflow Fundamentals Training Course

Kubeflow serves as a comprehensive toolkit designed to simplify, enhance portability, and ensure the scalability of Machine Learning (ML) applications on Kubernetes.

This live, instructor-led training, available both online and on-site, is tailored for developers and data scientists aiming 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 in both on-premise and cloud-based settings.
• Design, deploy, and manage ML workflows utilizing Docker containers and Kubernetes.
• Execute complete machine learning pipelines across varied architectures and cloud environments.
• Leverage Kubeflow to create and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads that span multiple platforms.

Course Format

• Interactive lectures paired with discussion sessions.
• An abundance of exercises and practical drills.
• Hands-on implementation within a live-lab environment.

Customization Options

• For tailored training on this course, please reach out to us to make arrangements.
• To explore Kubeflow further, please visit: https://github.com/kubeflow/kubeflow