Introduction to KNIME Analytics Platform
  • Course Overview
  • Installation and the KNIME Workspace
  • Installing KNIME Analytics Platform for Windows (Optional)
  • Installing KNIME Analytics Platform for Mac (Optional)
  • Installing KNIME Analytics Platform for Linux (Optional)
  • Virtual Tour Through KNIME Analytics Platform
  • The KNIME Analytics Platform Welcome Page
  • The KNIME Workbench
  • What is a Node? What is a Workflow?
  • The EXAMPLES Server
  • Workflows and Workflow Groups
  • The Node Repository
  • Importing and Exporting Workflows
  • Node Creation and Basic Commands
  • Data Table Structure
  • Annotations and Comments
  • Customizing KNIME Analytics Platform
  • Installing Extensions
  • Simple Metanodes and Wrapped Metanodes
  • Section 1 Multiple Choice
Data Blending
  • Introduction and Data Blending Demo
  • Data Access with KNIME
  • The KNIME Protocol
  • The Excel Reader Node
  • The File Reader Node
  • The Table Reader Node
  • The Join Operation and Methods
  • The Joiner Node (Part 1)
  • The Joiner Node (Part 2)
  • What is Concatenation?
  • The Concatenate Node
  • The Concatenate (Optional in) Node
  • Section 2 Multiple Choice
  • Section 2 Exercise Workflows
Data Manipulation and Aggregation
  • Introduction and Demo ETL Workflow
  • What is a Row Filter?
  • Row Filtering Based on Pattern Matching
  • Row Filtering Based on Numerical Values
  • Row Filtering Based on Row ID
  • What is a Column Filter?
  • The Column Filter Node
  • Data Manipulation: Numbers, Strings, and Rules
  • What is Data Aggregation?
  • The GroupBy Node
  • Advanced Aggregation with the GroupBy Node
  • The Pivoting Node
  • Pivoting with Multiple Columns
  • Pivoting with Complex Aggregation Methods
  • The CSV Writer Node
  • Section 3 Multiple Choice
  • Section 3 Exercise Workflows
Data Mining
  • Introduction and Classification Model Demo
  • The Learner / Predictor Motif
  • The Scorer (Javascript) Node
  • The Logistic Regression Algorithm
  • The Logistic Regression Learner Node (Part 1)
  • The Logistic Regression Learner Node (Part 2)
  • The Decision Tree Algorithm
  • The Decision Tree Learner Node
  • Section 4 Multiple Choice
  • Section 4 Exercise Workflows