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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation.
- Starting and customizing KNIME Analytics Platform.
- Nodes, data, and workflows.
- The data science cycle.
Module 2: Data Access
- Reading data from files.
- Accessing REST Services.
Module 3: ETL and Data Manipulation
- Row & Column filtering.
- Aggregators.
- Join & Concatenation.
- Transformation: Conversion, Replacement, Standardization, and New Feature Generation.
- Data Preparation for Time Series Analysis.
Day 2:
Module 4: Exporting Data
- Writing to a file.
- Generating a Report.
Module 5: Data Visualization
- Interactive Univariate Visual Exploration.
- Interactive Multivariate Visual Exploration.
-
Advanced Visualization Features.
Module 6: Predictive Analytics using KNIME
- Basic Data Mining Concepts.
- Regressions.
- Decision Tree Family.
- Model Evaluation.
Day 3:
Module 7: Controlling the flow
- Workflow Parameterization: Flow Variables.
- Re-executing Workflow Parts: Loops.
- Cleaning up your Workflow.
Module 8: Hands on KNIME Analytics Platform based Case Study
Requirements
Recommended
- A basic understanding of interpreting data.
- Experience with fundamental data processing.
Audience
- Data analysts.
- Data scientists.
- Business analysts.
21 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
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.
