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Certificate
Duration 21 hours
Course Outline
Day 1
Module 1: KNIME Analytics Platform: Introduction
- Installation procedures
- Launching and personalizing the KNIME Analytics Platform
- Nodes, data handling, and workflow architecture
- The data science lifecycle
Module 2: Data Access
- Reading data from files
- Connecting to REST Services
Module 3: ETL and Data Manipulation
- Filtering rows and columns
- Applying aggregators
- Joining and concatenating data sets
- Transformations: including conversion, replacement, standardization, and feature generation
- Preparing data for time series analysis
Day 2
Module 4: Data Export
- Writing output to files
- Generating reports
Module 5: Data Visualization
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
-
Advanced visualization capabilities
Module 6: Predictive Analytics with KNIME
- Foundational concepts of data mining
- Regression techniques
- Decision Tree algorithms
- Assessing model performance
Day 3
Module 7: Workflow Control
- Parameterizing workflows using Flow Variables
- Re-executing workflow segments via Loops
- Optimizing and cleaning workflow structures
Module 8: Practical Case Study using KNIME Analytics Platform
Requirements
Recommended
- A foundational ability to interpret and derive meaning from data.
- Familiarity with basic data processing concepts.
Audience
- Data analysts.
- Data scientists.
- Business analysts.
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.
