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 Duration 35 hours

Course Outline

  1. Introduction to Data Processing and Analysis
  2. Basic Information about the KNIME Platform
    • Installation and Configuration
    • Interface Overview
  3. Platform Overview in the Context of Tool Integration
  4. Getting Started: Creating Workflows
  5. Methodology for Business Model and Data Processing Creation
    • Documentation
    • Methods for Importing and Exporting Processes
  6. Overview of Basic Nodes
  7. Overview of ETL Processes
  8. Data Mining Methodologies
  9. Data Import Methodology
    • Importing Data from Files
    • Importing Data from Relational Databases Using SQL
    • Creating SQL Queries
  10. Overview of Advanced Nodes
  11. Data Analysis
    • Preparing Data for Analysis
    • Data Quality and Verification
    • Statistical Data Analysis
    • Data Modeling
  12. Introduction to Variables and Loops
  13. Building Advanced, Automated Processes
  14. Result Visualization
  15. Publicly Available and Free Data Sources
  16. Fundamentals of Data Mining
    • Overview of Selected Data Mining Tasks and Processes
  17. Knowledge Discovery from Data
    • Web Mining
    • SNA - Social Network Analysis
    • Text Mining - Document Analysis
    • Data Visualization on Maps
  18. Integration of Other Tools with KNIME
    • R
    • Java
    • Python
    • Gephi
    • Neo4j
  19. Report Building
  20. Training Summary

Requirements

Knowledge of the fundamentals of mathematical analysis.

Knowledge of the fundamentals of statistics.

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