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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation procedures for government systems
- Initiating and customizing the KNIME Analytics Platform environment
- Understanding nodes, data structures, and workflow architecture
- The data science lifecycle
Module 2: Data Access
- Reading data from local files
- Accessing REST APIs for external data sources
Module 3: ETL and Data Manipulation
- Filtering rows and columns
- Data aggregation techniques
- Joining and concatenating datasets
- Data transformation: conversion, replacement, standardization, and feature engineering
- Preparing data for time series analysis within a government context
Day 2:
Module 4: Exporting Data
- Writing data to files for secure storage
- Generating official reports and documentation
Module 5: Data Visualization
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
-
Advanced visualization capabilities
Module 6: Predictive Analytics using KNIME
- Fundamental concepts of data mining
- Regression analysis techniques
- Decision tree algorithms and applications
- Model evaluation and validation methods
Day 3:
Module 7: Controlling the flow
- Workflow parameterization using flow variables
- Re-executing workflow components via loop functions
- Optimizing and cleaning up workflow configurations
Module 8: Hands on KNIME Analytics Platform based Case Study
Requirements
Recommended Qualifications
- A foundational grasp of interpreting data for government purposes.
- Demonstrated proficiency in essential data processing methodologies.
Audience
- data analysts
- data scientists
- business analysts
21 Hours
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Equipped with examples