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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
- Overview of the platform in terms of tool integration
- Introduction to working with KNIME. Creating workflows
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Methodology for creating business models and data processing workflows
- documenting work
- methods for importing and exporting workflows
- Overview of basic nodes
- Overview of ETL processes
- Data exploration methodologies
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Data import methodologies
- 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 analysis of data
- data modeling
- Introduction to variables and loops
- Building advanced, automated workflows
- Visualizing results
- Publicly available and free data sources
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Data Mining Fundamentals
- 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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Integrating other tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Building reports
- Course 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.
