KNIME is hosting a one-day KNIME Server course during KNIME Fall Summit in Austin on November 5, 2019.
This course dives into the details of KNIME Server and KNIME WebPortal - discussing them from three different points of view: the power user, the administrator, and the end user. All tools and features designed for each one of these three personas are shown in detail and illustrated in interactive sessions and hands-on exercises.
Find out how to exchange workflows and data between the server and the client, how to take advantage of the many server dedicated nodes and features when implementing a workflow, how to set access rights on workflows, data, and metanodes, share metanodes, execute workflows remotely and from the KNIME WebPortal, and how to schedule report and workflow executions, and more.
The course is designed not only for customers, partners, and the community, but also for anyone interested in finding out more about the KNIME commercial platform and its functionalities.
- KNIME Product Overview
- Roles (Personas) involved in a Data Science Project
- Introduction to the Use Case (Customer Segmentation)
- KNIME Server Basic Features
- KNIME Server Advanced Features
- Summary and Q&A
- KNIME Course for Data Wranglers: Access, merge, transform, and inspect your data: Nov 5, 2019
- KNIME Analytics Platform for Beginners: From installation to utilization and everything in between: Nov 5, 2019
- Text Mining with KNIME Analytics Platform: Using the Textprocessing Extension: Nov 5, 2019
- KNIME Big Data Extensions: Data Mining with Apache Hive and Apache Spark: Nov 5, 2019
- KNIME Refresher Course: Master the Latest KNIME Features: Nov 5, 2019
- Advanced Users in KNIME Analytics Platform: Beyond the Basics: Nov 6, 2019
- Text Mining with KNIME Analytics Platform: Using the Textprocessing Extension: Nov 6, 2019
- KNIME Big Data Extensions: Data Mining with Apache Hive and Apache Spark: Nov 6, 2019
- KNIME Server Course: Nov 6, 2019
- KNIME Refresher Course: Master the Latest KNIME Features: Nov 6, 2019
- The Power of Random: Using Perturbation Experiments to Improve Model Accuracy and Interpretation: Nov 6, 2019