Kubeflow Fundamentals Training Course

Kubeflow serves as a comprehensive toolkit designed to streamline Machine Learning (ML) operations on Kubernetes, ensuring portability and scalability.

This live, instructor-led training session, available both online and onsite, is tailored for developers and data scientists looking to construct, deploy, and oversee machine learning workflows within a Kubernetes environment.

Upon completion, participants will possess the skills to:

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

Course Delivery Method

• Engaging lectures paired with interactive discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live lab environment.

Customization Possibilities

• Please reach out to us to discuss arranging a tailored training program for this course.
• For further information on Kubeflow, visit: https://github.com/kubeflow/kubeflow