Get in Touch
 Duration 35 hours

Course Outline

  1. Introduction to Data Processing and Analysis
  2. Fundamental Information Regarding the KNIME Platform
    • System Installation and Configuration
    • User Interface Orientation
  3. Platform Capabilities and Tool Integration Standards
  4. Fundamentals of Workflow Construction
  5. Methodologies for Developing Business Models and Data Processing Procedures
    • Technical Documentation Practices
    • Protocols for Importing and Exporting Processes
  6. Overview of Foundational Nodes
  7. Extraction, Transformation, and Loading (ETL) Process Summary
  8. Techniques for Data Exploration
  9. Data Ingestion Methodologies
    • Importing Data from File Systems
    • Retrieving Data from Relational Databases via SQL
    • Constructing SQL Queries
  10. Overview of Advanced Nodes
  11. Data Analysis Procedures
    • Preparing Data for Analytical Use
    • Data Quality Assurance and Validation
    • Statistical Analysis Techniques
    • Data Modeling Practices
  12. Application of Variables and Loop Structures
  13. Development of Advanced, Automated Processes
  14. Visualization of Analytical Results
  15. Publicly Available and Free Data Sources
  16. Fundamentals of Data Mining
    • Survey of Selected Data Mining Tasks and Processes
  17. Knowledge Discovery in Databases (KDD)
    • Web Mining Techniques
    • Social Network Analysis (SNA)
    • Text Mining and Document Analysis
    • Geospatial Data Visualization
  18. Integration of External Tools with KNIME
    • R Programming Language
    • Java Programming Language
    • Python Programming Language
    • Gephi Software
    • Neo4j Database
  19. Report Generation and Compilation
  20. Training Conclusion and Summary

Requirements

Proficiency in basic mathematical analysis is required.

Proficiency in fundamental statistical concepts is required.

Number of participants


Price per participant

Testimonials (2)

Upcoming Courses

Related Categories