KNIME Online Course for Beginners - May/June 2019

- - Online

This online course introduces the basic functionalities of KNIME Analytics Platform.

Mode: Interactive learning sessions and exercises, which are assigned at the end of each session and discussed at the beginning of the following session.
Who: This course has been designed for KNIME newbies who wish to know more about the basic functionalities of the platform. The four one-hour online lessons stretching over four weeks are ideal for aspiring KNIME experts whose time is limited.
Duration: One hour per week over 4 weeks, plus a one 15-minute course at the end
Location: Online
Dates: May 8, 15, 22, 29, June 5 - always at 6pm CEST
Price: EUR 250 + VAT

Course Content:

  • Session 1: Introduction to KNIME Analytics Platform
    What is KNIME? What is a workflow and how can we build a workflow to analyze our data?
  • Session 2: Data Import and Blending
    Data can be stored in different files and databases. How can we use KNIME to read EXCEL, JSON, or CSV files, read from a database or the web, and how can we combine the different resulting input tables into a single table?
  • Session 3: Data Manipulation, Aggregation, and Visualization
    Now that we have learned how to read data, we want to analyze it to gain further insights. What’s helpful here, are the different filtering and aggregation methods such as GroupBy and Pivoting. In addition, we learn how we can use KNIME to visualize data.
  • Session 4: Introduction to Data Mining
    How can we use machine learning in KNIME and which algorithms are good options for different tasks?

We will be using as the conferencing system, so please be aware that you need a stable and fast enough internet connection.

Please note: This course is capped at 25 participants, so please register early!

To take your KNIME knowledge to the next level, register for our KNIME Online Course for Advanced Users starting June 12, 2019. You'll learn more of the advanced steps such as loops, date&time integrations, parameter optimization, and more.