Kubeflow Fundamentals Training Course

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

This live, instructor-led training, available either online or on-site, is specifically tailored for developers and data scientists looking to develop, 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-premises and cloud environments.
• Construct, deploy, and manage ML workflows utilizing Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud platforms.
• Leverage Kubeflow to launch and administer Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads spanning multiple platforms.

Course Structure

• Interactive lectures paired with open discussions.
• Extensive exercises and practice sessions.
• Practical, hands-on implementation in a live laboratory setting.

Customization Possibilities

• For bespoke training requirements, please reach out to us to make arrangements.
• For further insights into Kubeflow, visit: https://github.com/kubeflow/kubeflow