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Certificate
Course Outline
Day 1:
Module 1: Introduction to KNIME Analytics Platform
- Installation process
- Launching and personalizing KNIME Analytics Platform
- Understanding nodes, data, and workflows
- The data science lifecycle
Module 2: Data Access
- Reading data from files
- Connecting to REST services
Module 3: ETL and Data Manipulation
- Filtering rows and columns
- Using aggregators
- Joining and concatenating datasets
- Data transformation: conversion, replacement, standardization, and feature generation
- Preparing data for time-series analysis
Day 2:
Module 4: Data Export
- Saving data to files
- Generating reports
Module 5: Data Visualization
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
-
Advanced visualization capabilities
Module 6: Predictive Analytics with KNIME
- Core concepts of data mining
- Regression analysis
- Decision tree algorithms
- Assessing model performance
Day 3:
Module 7: Workflow Control
- Parameterizing workflows using Flow Variables
- Re-running workflow segments using Loops
- Organizing and optimizing workflows
Module 8: Practical Case Study using KNIME Analytics Platform
Requirements
Recommended Background
- A fundamental grasp of interpreting data.
- Familiarity with basic data processing techniques.
Intended Audience
- Data analysts
- Data scientists
- Business analysts
21 Hours
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
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.
