Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Certificate
Duration 14 hours
Course Outline
Introduction
Initiating the KNIME Workflow
- Definition of KNIME
- KNIME Analytics Platform
- KNIME Server Infrastructure
Machine Learning Fundamentals
- Theoretical foundations of computational learning
- Algorithmic approaches to computational experience
Development Environment Configuration
- Installation and system setup of KNIME
KNIME Node Management
- Integration of nodes into workflows
- Data retrieval and parsing
- Consolidation, segmentation, and data filtering
- Grouping and pivot table creation
- Data purification and quality assurance
Modeling Processes
- Workflow architecture and design
- Data ingestion procedures
- Data preprocessing for analysis
- Data visualization techniques
- Development of decision tree models
- Application of regression modeling
- Data forecasting and prediction
- Data comparison and reconciliation
Advanced Learning Methodologies
- Application of random forest algorithms
- Polynomial regression implementation
- Class assignment strategies
- Model performance evaluation
Summary and Conclusions
Requirements
- Proficiency in Python
- Proficiency in 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)
Equipped with examples