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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)
Understanding big data beter
Shaune Dennis - Vodacom
Course - Big Data Business Intelligence for Telecom and Communication Service Providers
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
La capacitacidad de la herramienta
Gerardo Avila - Reckitt Benckizer
Course - KNIME Analytics Platform for BI
The example and training material were sufficient and made it easy to understand what you are doing.