This course builds on the [L1-AP] Data Literacy with KNIME Analytics Platform - Basics by introducing advanced concepts for building and automating workflows with KNIME Analytics Platform Version 5.
This course covers topics for controlling node settings and automating workflow execution. You will learn concepts such as flow variables, loops, switches, and how to catch errors. In addition, you will learn how to handle date and time data, how to create advanced dashboards, and how to process data within a database.
Moreover, this course introduces basic concepts of data science. You will learn how to train, apply and evaluate a supervised machine learning (ML) model. Moreover, this course also covers how to optimize and validate your ML model. The course concludes with unsupervised learning with K-means clustering as an example.
This is an instructor-led course consisting of four, 75 minutes online sessions run by our data scientists. Each session has an exercise for you to complete at home, and we will go through the solution at the start of the following session. The course concludes with a 15-30 minutes wrap up session.
Session 1: Flow Variables & Components
Session 2: Workflow Control and Invocation
Session 3: Date&Time, Databases, REST Services, Python & R Integration
Session 4: Introduction to Machine Learning
Session 5: Review of the Last Exercises and Q&A