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Certificate
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 (3)
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)
Very useful in because it helps me understand what we can do with the data in our context. It will also help me