Kubeflow Fundamentals Training Course

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

This live, instructor-led course, available both online and onsite, is tailored for developers and data scientists seeking to construct, deploy, and oversee machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow in on-premise and cloud-based setups.
• Create, deploy, and oversee ML workflows utilizing Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud ecosystems.
• 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.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory setting.

Customization Availability

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