Data Science Implementation Management using KNIME Server Training Course


KNIME Server is the enterprise software for team-based collaboration, automation, management, and deployment of data science workflows as analytical applications and services.

By the end of this training, participants will be able to:

  • Schedule analytics workflows to run automatically and give yourself more time to focus on data science.
  • Control workflows to automate model management
  • Scale and pin workflow execution with well provisioned, high performance server architecture which is configured to your specifications.
  • Design, edit, and execute workflows on KNIME Server using the remote workflow editor and take advantage of well provisioned hardware in a secure environment.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course or to know more on this program, please contact us to arrange.



NobleProg and KNIME design, build and deliver end-to-end advanced analytics solutions that are customized to each customer’s business needs.

By combining KNIME’s leading open solution for data driven innovation with NobleProg’s domain and technical expertise in analytics, we help our customers reduce costs and gain data-driven insights for better business outcomes.


  • A basic understanding of making sense of the data.
  • Experience with fundamental data processing.


  • data science managers
  • model administrators
  • data engineers
  • data analysts
  • data scientists

Course Outline

Day 1:

  • Introduction

Module 1: KNIME Server:

Collaboration – Connecting and Deploying Items to KNIME Server from KNIME Analytics Platform

  • How to Connect to KNIME Server
  • Permission Settings on KNIME Server

Module 2: KNIME Server: Automation & Deployment

Automation and Deployment – Remote Execution and KNIME WebPortal

  • Remote Execution on KNIME Server
  • KNIME Remote Workflow Editor
  • KNIME WebPortal

Day 2:

Module 3: KNIME Server: Management

Management – Versioning and Workflow Difference

  • Versioning
  • Workflow Comparison
  • Node Comparison

Module 4: Overview of KNIME Analytics Platform

  • Controlling the model flow
  • Model deployment on KNIME Server
  • Test Scenarios between KNIME AP & Server
  • Summary and Conclusion

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