Learning Path

Getting started with Kubeflow Pipelines

An end-to-end open source platform to orchestrate ML workflows on Kubernetes

Archived content

Archive date: 2024-06-25

This content is no longer being updated or maintained. The content is provided “as is.” Given the rapid evolution of technology, some content, steps, or illustrations may have changed.

Overview

This learning is designed to help you get a foot into the door of machine learning (ML) automation by using Kubeflow Pipelines to orchestrate ML workflows.

Skill level

Beginner

Estimated time to complete

Approximately 1 hour.

Learning objectives

  • Understand the fundamental concepts for Kubeflow Pipelines
  • Learn how to deploy Kubeflow Pipelines
  • Learn how to compose and run a simple pipeline
  • Learn how to automate prompt tuning for large language models (LLMs)
  • Learn how to serve large language models (LLMs) on KServe ModelMesh with Kubeflow Pipelines