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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation
- Launching and customising 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 and column filtering
- Aggregators
- Joining and 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
- Fundamental 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 foundational understanding of interpreting data.
- Experience with basic 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.
