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Certificate
Duration 21 hours
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Introduction
- Installation process.
- Launching and tailoring KNIME Analytics Platform.
- Understanding Nodes, data, and workflows.
- The data science lifecycle.
Module 2: Data Retrieval
- Reading Data from files.
- Connecting to REST Services.
Module 3: ETL and Data Transformation
- Filtering Rows & Columns.
- Using Aggregators.
- Joining & Concatenating data.
- Transformations: Conversion, Replacement, Standardization, and Generating New Features.
- Preparing Data for Time Series Analysis.
Day 2:
Module 4: Data Export
- Saving to a file.
- Creating Reports.
Module 5: Visualizing Data
- Interactive Univariate Visual Analysis.
- Interactive Multivariate Visual Analysis.
-
Advanced Visualization Capabilities
Module 6: Predictive Analytics with KNIME
- Foundational Data Mining Concepts.
- Regression Analysis.
- Decision Tree Algorithms.
- Assessing Model Performance.
Day 3:
Module 7: Managing Flow Control
- Workflow Parameterization using Flow Variables.
- Re-running Workflow Segments: Loops.
- Optimizing and Organizing Your Workflow.
Module 8: Practical Case Study using KNIME Analytics Platform
Requirements
Recommended Background
- A foundational understanding of interpreting data.
- Experience with basic data processing techniques.
Target 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.
