In this course, you will :
- Demonstrates how KNIME supports all phases of the Cross Industry Standard Process for Data Mining (CRISP-DM) in a single platform.
- Get started quickly—in 15 minutes or less—or stay for in-depth training on merging and aggregation, modelling, and data scoring.
- Learn how to extend KNIME's capabilities and integrate R and Python.
1. How Does KNIME Complement Your Existing Analytics Toolkit?
- Why use an Analytics Workbench?
- Using CRISP-DM to evaluate tools
- Why choose KNIME?
2. Getting Comfortable with KNIME
- The KNIME interface
- Find case studies on the Examples Server
- Add thousands of nodes with Extensions
- Search and Help
3. Accessing Data
- Accessing data
- File reader node
4. Data Understanding
- Describe data and verify data quality
- Explore data: Scatterplot
- Explore data: Boxplot
5. Data Integration and Merging
- Merging with the Joiner node
- Aggregating with the GroupBy node
- Creating new variables with Construct
- Select data with Column Filter
- Balancing data with Row Sampling node
- Clean data with the Missing Value node
- Format with Cell Splitter
- KNIME modeling options
- Regression example
- Decision tree
- Decision tree: Scoring new data
7. A World of Possibilities
- R and GGPLOT2
- Other options