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Course Outline
- Introduction to Data Processing and Analysis
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Basic Information about the KNIME Platform
- installation and configuration
- interface overview
- Platform Overview in Terms of Tool Integration
- Introduction to Workflow Creation
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Methodology for Creating Business Models and Data Processing Processes
- documentation
- methods for importing and exporting processes
- Overview of Basic Nodes
- ETL Process Overview
- Data Exploration Methodologies
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Data Import Methodology
- data import from files
- data import from relational databases using SQL
- creating SQL queries
- Overview of Advanced Nodes
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Data Analysis
- data preparation for analysis
- data quality and validation
- statistical data analysis
- data modeling
- Introduction to Variable Usage and Loops
- Building Advanced, Automated Processes
- Visualization of Results
- Public and Free Data Sources
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Basics of Data Mining
- Overview of Selected Types of Data Mining Tasks and Processes
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Knowledge Discovery from Data
- Web Mining
- SNA - Social Networks
- Text Mining - Document Analysis
- Data Visualization on Maps
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Integration of Other Tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Report Building
- Training Summary
Requirements
Knowledge of basic mathematical analysis.
Knowledge of basic statistics.
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.
