Online Course

[L4-CA] Machine Learning for Chemical Applications - Online

- - Online
[L4-CA] Machine Learning for Chemical Applications - Online

Learn to build advanced cheminformatics workflows in an interactive hands-on setting using KNIME Analytics Platform and its Cheminformatics Extensions. 

This online course will contain several units where we'll cover a diverse set of topics such as data wrangling, interactive filtering of compounds and their exploration, machine learning for virtual screening, multi-objective optimization, and matched molecular pair analysis. After completing this course you'll have a set of fully functional workflows and will have learned how to build your own advanced applications. 
This is an instructor-led course consisting of four 75-minute online sessions, each session has an exercise for you to complete at home, we will go through the solution at the start of the following session. The course concludes with a 15-minute wrap up session. 

Course Content

  • Session 1: Access and Transformation of Chemical Data

  • Session 2: Machine Learning

  • Session 3: Multi-objective Optimization

  • Session 4: Matched Molecular Pair Analysis

  • Session 5: Discussion of the Last Exercises and Q&A

Download agenda


What level of KNIME experience is needed for this course?

We assume that you have basic KNIME knowledge already but you don't need to be an expert. 

How do I join the course?

You’ll receive a zoom link with your registration confirmation. Make sure you have a stable internet connection!

What if I miss a session? Will I be able to watch a replay?

Sure! The sessions will be recorded and you’ll have access to each one for one month from the time the session is over.

Will I be able to ask questions?

Absolutely - fire away!

What do I need to have?

Your own laptop, ideally with the latest version of KNIME Analytics Platform (v4.6) already installed.

Where do I find the latest version of KNIME Analytics Platform?

Download the latest free, open source version of KNIME here:

What other resources will help me to get started with KNIME?
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