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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation
- Launching and customizing KNIME Analytics Platform
- Nodes, data, and workflows
- The data science lifecycle
Module 2: Data Access
- Reading data from files
- Accessing REST Services
Module 3: ETL and Data Manipulation
- Filtering rows and columns
- Aggregation tools
- Joining and concatenating data
- Transformations: Conversion, Replacement, Standardization, and Feature Generation
- Preparing data for Time Series Analysis
Day 2:
Module 4: Exporting Data
- Writing to a file
- Generating Reports
Module 5: Data Visualization
- Interactive Univariate Visual Exploration
- Interactive Multivariate Visual Exploration
-
Advanced Visualization Features
Module 6: Predictive Analytics using KNIME
- Fundamental Concepts of Data Mining
- Regression Techniques
- Decision Tree Family
- Model Evaluation
Day 3:
Module 7: Controlling Workflow
- Workflow Parameterization: Flow Variables
- Re-executing Workflow Parts: Loops
- Cleaning up your Workflow
Module 8: Hands-on KNIME Analytics Platform Case Study
Requirements
Recommended
- A fundamental 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.
