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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation
- Launching and customizing KNIME Analytics Platform
- 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
- Row & Column filtering
- Aggregators
- Join & Concatenation
- Transformation: Conversion, Replacement, Standardization, and Feature Generation
- Preparing data for Time Series Analysis
Day 2:
Module 4: Data Export
- Writing to a file
- Report Generation
Module 5: Data Visualization
- Interactive Univariate Visual Exploration
- Interactive Multivariate Visual Exploration
-
Advanced Visualization Features
Module 6: Predictive Analytics using KNIME
- Fundamentals of Data Mining
- Regressions
- Decision Tree Family
- Model Evaluation
Day 3:
Module 7: Flow Control
- Workflow Parameterization: Flow Variables
- Re-executing Workflow Parts: Loops
- Workflow Cleanup
Module 8: Hands-on KNIME Analytics Platform Case Study
Requirements
Recommended
- A foundational understanding of data interpretation.
- Familiarity 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
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Tshering Dorji - Druk Holding and Investments
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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.
