Kubeflow Fundamentals Training Course

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

Delivered by an instructor in a live setting (either online or on-site), this training is tailored for developers and data scientists aiming to construct, deploy, and oversee machine learning workflows within a Kubernetes environment.

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

• Install and configure Kubeflow both on-premises and in cloud environments.
• Create, deploy, and manage ML workflows utilizing Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud infrastructures.
• Leverage Kubeflow to launch and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads spanning multiple platforms.

Course Format

• Engaging lectures paired with interactive discussions.
• Extensive exercises and practical application.
• Live, hands-on implementation in a laboratory environment.

Customization Options

• For a tailored training experience, please contact us to discuss requirements.
• To explore Kubeflow further, visit: https://github.com/kubeflow/kubeflow