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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Introduction
- Installation
- Launching and customizing KNIME Analytics Platform
- Nodes, data, and workflows
- 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
- Aggregation techniques
- Joining and concatenating data
- Transformations: Conversion, Replacement, Standardization, and Feature Generation
- Preparing data for Time Series Analysis
Day 2:
Module 4: Data Export
- Writing data to a file
- Creating reports
Module 5: Data Visualization
- Interactive Univariate Visual Exploration
- Interactive Multivariate Visual Exploration
-
Advanced Visualization Capabilities
Module 6: Predictive Analytics with KNIME
- Fundamental Concepts in Data Mining
- Regression analysis
- Decision Tree algorithms
- Model assessment
Day 3:
Module 7: Flow Control
- Workflow Parameterization: Flow Variables
- Re-running Workflow Segments: Loops
- Organizing your Workflow
Module 8: Practical KNIME Analytics Platform Case Study
Requirements
Suggested Background
- A foundational understanding of interpreting data.
- 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
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.
