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Course Outline
- Introduction to Data Processing and Analysis
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Overview of the KNIME Platform
- Installation and Configuration
- Interface Overview
- Platform Overview with a Focus on Tool Integration
- Getting Started: Creating Workflows
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Methodologies for Building Business Models and Data Processing Processes
- Documentation
- Methods for Import and Export of Processes
- Overview of Basic Nodes
- Overview of ETL Processes
- Data Mining Methodologies
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Data Import Methodologies
- Importing Data from Files
- Importing Data from Relational Databases Using SQL
- Writing SQL Queries
- Overview of Advanced Nodes
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Data Analysis
- Preparing Data for Analysis
- Data Quality and Validation
- Statistical Data Analysis
- Data Modeling
- Introduction to Variables and Loops
- Building Advanced, Automated Processes
- Visualization of Results
- General-Purpose and Free Data Sources
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Data Mining Basics
- Overview of Selected Data Mining Tasks and Processes
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Knowledge Discovery from Data
- Web Mining
- SNA – Social Network Analysis
- 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
Familiarity with the fundamentals of mathematical analysis.
Familiarity with the basics of 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
Radomir was very patient and helpful when I got stuck. He was very knowledgeable about the subject matter, and his explanations on different concepts were detailed and thorough.
Rachel Turcan - Animal and Plant Health Agency
Course - ArcGIS for Spatial Analysis
It's a hands-on session.
