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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation procedures.
- Launching and customizing the KNIME Analytics Platform.
- Understanding Nodes, Data, and Workflows.
- Exploring the data science lifecycle.
Module 2: Data Access
- Reading data from files.
- Accessing REST Services.
Module 3: ETL and Data Manipulation
- Filtering by Rows and Columns.
- Utilizing Aggregators.
- Joining and Concatenating data.
- Data Transformation: Conversion, Replacement, Standardization, and Feature Generation.
- Preparing Data for Time Series Analysis.
Day 2:
Module 4: Exporting Data
- Writing data to files.
- Generating Reports.
Module 5: Data Visualization
- Interactive Univariate Visual Exploration.
- Interactive Multivariate Visual Exploration.
-
Advanced Visualization Features
Module 6: Predictive Analytics using KNIME
- Core Concepts of Data Mining.
- Regression Techniques.
- The Decision Tree Family.
- Model Evaluation Methods.
Day 3:
Module 7: Controlling the Flow
- Workflow Parameterization: Using Flow Variables.
- Re-executing Workflow Parts: Implementing Loops.
- Cleaning up your Workflow.
Module 8: Hands-on KNIME Analytics Platform Based Case Study
Requirements
Recommended
- A fundamental understanding of interpreting data.
- Experience with basic data processing techniques.
Target 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.
