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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation process.
- Launching and customizing the KNIME Analytics Platform.
- Understanding nodes, data, and workflows.
- The data science lifecycle.
Module 2: Data Access
- Reading data from files.
- Accessing REST Services.
Module 3: ETL and Data Manipulation
- Row and column filtering.
- Using aggregators.
- Joining and concatenation.
- Transformation: Conversion, replacement, standardization, and new feature generation.
- Preparing data for time series analysis.
Day 2:
Module 4: Exporting Data
- Writing data to files.
- Generating reports.
Module 5: Data Visualization
- Interactive univariate visual exploration.
- Interactive multivariate visual exploration.
- Advanced visualization features.
Module 6: Predictive Analytics Using KNIME
- Basic data mining concepts.
- Regression analysis.
- The decision tree family.
- Model evaluation techniques.
Day 3:
Module 7: Controlling the Workflow
- Workflow parameterization: Flow variables.
- Re-executing parts of a workflow: Loops.
- Cleaning up your workflow.
Module 8: Hands-on KNIME Analytics Platform Case Study
Requirements
Recommended Prerequisites
- A fundamental understanding of interpreting data.
- Experience with basic data processing techniques.
Target Audience
- Data analysts
- Data scientists
- Business analysts
21 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
