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

  • 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
 

Requirements

Recommended

  • A basic understanding of making sense of the data.
  • Experience with fundamental data processing.

Audience

  • data analysts
  • data scientists
  • business analysts
  21 Hours
 

Testimonials (4)

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