• Online
April 19, 20, 21, 22: 5 - 6:15 PM UTC +2 (Berlin)
April 23, 2021: 5 PM - 5:15 PM UTC +2 (Berlin)
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.
Course Content:
• 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
The course fee is 50€ + VAT.
Learning goals:
Usage of KNIME in Life Science, Data Manipulation, Visualization, Exploration, Similarity Search
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 need your own laptop, ideally pre-installed with the latest version of KNIME Analytics Platform, which you can download at knime.com/downloads.
Data Science, Life Science, KNIME, Exploration
Alexander Fillbrunn
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