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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation
- 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 datasets
- Transformations: Conversion, Replacement, Standardization, and New Feature Generation
- Preparing data for time series analysis
Day 2:
Module 4: Data Export
- Writing data to files
- Generating reports
Module 5: Data Visualization
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
-
Advanced visualization features
Module 6: Predictive Analytics using KNIME
- Fundamental data mining concepts
- Regression analysis
- Decision Tree algorithms
- Model evaluation techniques
Day 3:
Module 7: Flow Control
- Workflow parameterization via Flow Variables
- Re-executing workflow segments using Loops
- Optimizing and cleaning workflows
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.
