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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 walkthrough
- Platform overview in the context of tool integration
- Introduction to Work. Creating Workflows
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Methodology for creating business models and data processing processes
- Work documentation
- Process import and export methods
- 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 examination
- Data modeling
- Introduction to variables and loops
- Building advanced, automated processes
- Visualizing results
- Publicly available and free data sources
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Data Mining Basics
- Overview of selected Data Mining task types 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
Basic knowledge of mathematical analysis.
Basic knowledge of statistics.
35 Hours
Testimonials (2)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
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.
