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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
- Overview of the Interface
- Overview of the Platform in Terms of Tool Integration
- Introduction to Work and Creating Workflows
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Methodology for Creating Business Models and Data Processing Processes
- Work Documentation
- Import and Export Methods for Processes
- Overview of Basic Nodes
- Overview of ETL Processes
- Data Mining 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 Data Exploration
- Data Modeling
- Introduction to Using Variables and Loops
- Building Advanced, Automated Processes
- Visualization of Results
- Public and Free Data Sources
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Data Mining Basics
- Overview of Selected Types of Data Mining Tasks and Processes
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Discovering Insights 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
Knowledge of the basics of mathematical analysis.
Knowledge of the basics of statistics.
35 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
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.
