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Course Outline
- Introduction to data processing and data analysis
- Fundamental information of KNIME platform
- Installation and configuration
- Overview of the interface
- Discussion of tool integration
- Building workflows
- Methodology of creating business models and data modeling
- Documentation
- import and export workflows
- Basic nodes
- Design ETL processes
- Data mining
- Data Import
- from files
- from relational databases using SQL
- creating SQL queries
- Advanced nodes
- Data analysis:
- data preparation
- data check-up
- statistical data examination
- data modeling
- Introduction to Flow Variables and Loops
- Advanced process automation
- Visualization Features
- Open source data sources
- Data mining basics
- selected types of Data Mining tasks and processes
- Getting more knowledge from data
- Web Mining
- SNA
- Text Mining
- Data visualization on graphs
- Install Extensions and Integrations
- R
- Java
- Python
- Gephi
- Neo4j
- Reporting
- Overview
- BIRT Integration
- KNIME WebPortal
- Conclusion and Q&A session
Requirements
Analytical thinking approach.
Basics of statistics and mathematical analysis.
35 Hours
Testimonials (3)
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.
Ian - Archeoworks Inc.
Course - ArcGIS Fundamentals
The thing I liked the most about the training was the organization and the location
Hamid Tuama - Ability with Innovation General Contracting (DMCC Branch)
Course - ArcGIS for Spatial Analysis
It's a hands-on session.
