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Duration 35 hours
Course Outline
- Introduction to data processing and analysis
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Basic information about the KNIME platform
- Installation and configuration
- Interface overview
- Overview of the platform in terms of tool integration
- Introduction to practical work. Creating workflows
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Methodology for creating business models and data processing processes
- Work documentation
- Methods for importing and exporting processes
- Overview of basic nodes
- Overview of ETL processes
- 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
- Preparing data for analysis
- Data quality and validation
- Statistical analysis of data
- Data modeling
- Introduction to the use of variables and loops
- Building advanced, automated processes
- Visualization of results
- Publicly available and free data sources
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Data Mining fundamentals
- Overview of selected types of 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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Integrating other tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Building reports
- Training summary
Requirements
Familiarity with the fundamentals of mathematical analysis.
Familiarity with statistical fundamentals.
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.
