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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 Workflows. 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
- Data Exploration 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 validation
- Statistical analysis of data
- Data modeling
- Introduction to Variables and Loops
- Building Advanced, Automated Processes
- Visualizing 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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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
Familiarity with the fundamentals of mathematical analysis.
Familiarity with the fundamentals of statistics.
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.
