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Certificate
Course Outline
Day 1
Module 1: Overview of the KNIME Analytics Platform
- Installation procedures.
- Launching and customizing the KNIME Analytics Platform.
- Understanding nodes, data, and workflows.
- The data science lifecycle.
Module 2: Data Access
- Reading data from files.
- Interacting with REST services.
Module 3: ETL and Data Manipulation
- Filtering rows and columns.
- Using aggregators.
- Joining and concatenating data.
- Transformations: 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 Features
Module 6: Predictive Analytics with KNIME
- Foundational concepts in Data Mining.
- Regression techniques.
- The Decision Tree family of algorithms.
- Model evaluation methods.
Day 3
Module 7: Workflow Control
- Workflow Parameterization: Utilizing Flow Variables.
- Re-executing Workflow Parts: Implementing Loops.
- Workflow cleanup and organization.
Module 8: Hands-on Case Study with the KNIME Analytics Platform
Requirements
Recommended
- A foundational understanding of data interpretation.
- Experience with basic data processing techniques.
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.
