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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 regarding tool integration
- Getting Started: Creating Workflows
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Methodology for Business Modelling and Data Processing
- Documentation
- Import and export methods for processes
- Overview of basic nodes
- Overview of ETL processes
- Data Mining Methodologies
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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 verification
- Statistical data analysis
- Data modelling
- Introduction to using variables and loops
- Building advanced, automated processes
- Visualisation of results
- Public and free data sources
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Fundamentals of Data Mining
- Overview of selected types of Data Mining tasks and processes
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Discovering Knowledge from Data
- Web Mining
- SNA – Social Networks
- Text Mining – Document Analysis
- Data visualisation on maps
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Integration of other tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Report Generation
- 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.
