This course builds on the [L1-LS] KNIME Analytics Platform for Data Scientists (Life Science): Basics by introducing advanced data science concepts using Life Science examples.
Learn all about flow variables, different workflow controls such as loops, switches, and error handling. Find out how to automatically find the best parameter settings for your machine learning model, get a taste for ensemble models, parameter optimization, and cross validation and see how Date/Time integrations work.
This is an instructor-led course consisting of four, 75-minutes online sessions run by one of our KNIME data scientists. Each session has an exercise for you to complete at home and together, we will go through the solution at the start of the following session. The course concludes with a 15-minute wrap up session.
This course is partially supported by de.NBI: the German Network for Biofinformatics Infrastructure.
- Session 1: Flow Variables
- Session 2: Workflow Control - Loops, Switch and Try Catch
- Session 3: Advanced Machine Learning - Ensemble Models, Parameter Optimization, and Cross Validation
- Session 4: Integrated Deployment & Date/Time Data
You should be an advanced KNIME user and ideally have already built some workflows. This course doesn’t provide an introduction to KNIME Analytics Platform - it focuses on more advanced data science concepts.
You'll receive a zoom link in a separate email a few days before the course starts. Make sure you have a stable internet connection!
Sure! The sessions will be recorded and you’ll have access to each one for one month from the time the session is over.
Absolutely - fire away!
Your own laptop, ideally pre-installed with the latest version of KNIME Analytics Platform, which you can download at knime.com/downloads.