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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
    • Overview of the interface
  3. Overview of the platform in terms of tool integration
  4. Getting started. Creating workflows
  5. Methodology for creating business models and data processing processes
    • Work documentation
    • Methods for importing and exporting processes
  6. Overview of basic nodes
  7. Overview of ETL processes
  8. Data exploration methodologies
  9. Data import methods
    • 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 validation
    • Statistical data analysis
    • Data modeling
  12. Introduction to using variables and loops
  13. Building advanced, automated processes
  14. Visualization of results
  15. Open and free data sources
  16. Fundamentals of Data Mining
    • Overview of selected types of tasks and processes in Data Mining
  17. Knowledge discovery from data
    • Web Mining
    • SNA – social networks
    • Text Mining – document analysis
    • Data visualization on maps
  18. Integration of other tools with KNIME
    • R
    • Java
    • Python
    • Gephi
    • Neo4j
  19. Building reports
  20. Summary of the training

Requirements

Knowledge of fundamental calculus.

Knowledge of basic statistics.

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