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

• Read Data from file
• 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

• Write 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

• Data Mining Basic 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