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Certificate
Course Outline
Day 1:
Module 1: Overview of KNIME Analytics Platform
- Installation
- Launching and customizing KNIME Analytics Platform
- Nodes, data, and workflows
- The data science lifecycle
Module 2: Data Access
- Reading data from files
- Accessing REST Services
Module 3: ETL and Data Manipulation
- Row & Column filtering
- Aggregation techniques
- Joins and Concatenation
- Transformation: Conversion, Replacement, Standardization, and Feature Generation
- Preparing data for Time Series Analysis
Day 2:
Module 4: Data Export
- Writing to files
- Report generation
Module 5: Data Visualization
- Interactive Univariate Visual Exploration
- Interactive Multivariate Visual Exploration
-
Advanced Visualization Features
Module 6: Predictive Analytics with KNIME
- Fundamental Data Mining Concepts
- Regression analysis
- Decision Tree algorithms
- Model evaluation methods
Day 3:
Module 7: Workflow Control
- Workflow Parameterization using Flow Variables
- Re-executing Workflow Parts via Loops
- Organizing and cleaning up Workflows
Module 8: Practical Case Study using KNIME Analytics Platform
Requirements
Recommended Background
- A fundamental understanding of data interpretation.
- Experience with basic data processing techniques.
Target Audience
- Data analysts
- Data scientists
- Business analysts
21 Hours
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.
