Certificate
Course Outline
Introduction
Getting Started with KNIME
- What is KNIME?
- KNIME Analytics Platform
- KNIME Server
Machine Learning Fundamentals
- Computational learning theory
- Algorithms for computational tasks
Setting Up the Development Environment
- Installing and configuring KNIME
Working with KNIME Nodes
- Adding nodes to workflows
- Accessing and reading data sources
- Merging, splitting, and filtering datasets
- Grouping and pivoting data
- Data cleaning techniques
Modeling Process
- Creating workflows
- Importing data
- Data preparation
- Data visualization
- Building a decision tree model
- Working with regression models
- Making predictions
- Comparing and matching data
Advanced Learning Techniques
- Utilizing random forest methods
- Applying polynomial regression
- Assigning classes
- Model evaluation
Summary and Conclusion
Requirements
- Proficiency in Python
- Experience with R
Intended Audience
- Data Scientists
Testimonials (3)
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
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
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.
