Databricks & KNIME for Machine Learning - Getting Started

You'll start by exploring the key features of both KNIME and Databricks and how they integrate. Then, you’ll learn how to access and process Databricks data from within KNIME, and how to use no-code workflows to train and deploy machine learning models at scale using Databricks’ computing power—all without writing code.

Once you have completed this course, you will be able to:

• Integrate Databricks into KNIME’s intuitive visual workflows.
• Process large-scale data and train scalable machine learning models using Databricks compute with KNIME’s no-code Spark nodes.
• Automate Databricks-integrated workflows or deploy as data apps or REST services.

This is an on-demand online course you can take at any time covering the following topics:

Introduction to Key Concepts and Functionalities of Databricks and KNIME

• Why KNIME for Databricks?
• KNIME Databricks integration

Process Unity Catalog Data with Spark

• Processing Databricks data with no-code Spark nodes
• Prototyping Spark workflows locally

Scalable Machine Learning on Databricks Data

• Learner-Predictor motif for machine learning models training in KNIME
• Training machine learning models with Spark
• Deploy a machine learning model into production

The course concludes with a knowledge check. Upon successful completion, you will earn a microcredential.

For more information on KNIME and Databricks partnership, please check out this page.