Kubeflow Fundamentals Training Course

Kubeflow serves as a comprehensive toolkit designed to simplify, facilitate portability, and enable scalability for Machine Learning (ML) operations on Kubernetes.

This live training session, led by an instructor and available either online or on-site, is specifically tailored for developers and data scientists aiming to construct, deploy, and oversee machine learning workflows within Kubernetes environments.

Upon completion of this training, participants will gain the ability to:

• Install and configure Kubeflow in both on-premise and cloud-based settings.
• Construct, deploy, and manage ML workflows utilizing Docker containers and Kubernetes.
• Execute end-to-end machine learning pipelines across various architectures and cloud platforms.
• Utilize Kubeflow to create and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.

Course Format

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

Course Customization Options

• For a customized training experience, please reach out to us to make arrangements.
• For further information on Kubeflow, please visit: https://github.com/kubeflow/kubeflow