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Course Outline

Day 1:

Module 1: Overview of the KNIME Analytics Platform for Government

  • Installation and Configuration
  • Launching and Customizing the KNIME Analytics Platform
  • Understanding Nodes, Data, and Workflows
  • The Data Science Lifecycle

Module 2: Data Access for Government

  • Importing Data from Files
  • Accessing REST Services

Module 3: ETL and Data Manipulation for Government

  • Row and Column Filtering
  • Aggregation Techniques
  • Joining and Concatenating Data
  • Transformation: Conversion, Replacement, Standardization, and Feature Engineering
  • Preparing Data for Time Series Analysis

Day 2:

Module 4: Exporting Data for Government

  • Writing Data to a File
  • Generating Reports

Module 5: Data Visualization for Government

  • Interactive Univariate Visual Exploration
  • Interactive Multivariate Visual Exploration
  • Advanced Visualization Features

Module 6: Predictive Analytics Using KNIME for Government

  • Fundamental Concepts of Data Mining
  • Regression Techniques
  • Decision Tree Models
  • Model Evaluation and Validation

Day 3:

Module 7: Controlling Workflow Execution for Government

  • Parameterizing Workflows: Flow Variables
  • Re-executing Workflow Segments: Loops
  • Optimizing and Cleaning Up Workflows

Module 8: Case Study Using the KNIME Analytics Platform for Government
 

Requirements

Recommended

  • A foundational understanding of data interpretation.
  • Experience with basic data processing techniques.

Audience

  • Data analysts
  • Data scientists
  • Business analysts

These recommendations are designed to enhance the skills of professionals for government and public sector data management roles.

 21 Hours

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