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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
- overview of the interface
- Overview of the Platform in Terms of Tool Integration
- Getting Started. Creating Workflows
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Methodology for Creating Business Models and Data Processing Processes
- documentation of work
- methods for importing and exporting processes
- Overview of Basic Nodes
- Overview of ETL Processes
- Methodologies for Data Exploration
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Data Import Methodology
- importing data from files
- importing data from relational databases using SQL
- creating 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 Using Variables and Loops
- Building Advanced, Automated Processes
- Visualization of Results
- Public and Free Data Sources
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Fundamentals of Data Mining
- 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
- Building Reports
- Training Summary
Requirements
Knowledge of the fundamentals of mathematical analysis.
Knowledge of the fundamentals 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.
