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Certificate
Duration 21 hours
Course Outline
Day 1
Module 1: KNIME Analytics Platform: Overview
- Installation
- Launching and customising KNIME Analytics Platform
- Nodes, data, and workflows
- The data science cycle
Module 2: Data Access
- Reading data from files
- Accessing REST services
Module 3: ETL and Data Manipulation
- Row and column filtering
- Aggregators
- Join and concatenation
- Transformation: Conversion, Replacement, Standardisation, and New Feature Generation
- Data preparation for time series analysis
Day 2
Module 4: Exporting Data
- Writing to a file
- Generating a report
Module 5: Data Visualisation
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
- Advanced visualisation 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 parameterisation: Flow variables
- Re-executing workflow parts: Loops
- Tidying up your workflow
Module 8: Hands-on KNIME Analytics Platform-based Case Study
Requirements
Recommended
- A basic understanding of deriving meaning from data.
- Experience with fundamental data processing.
Audience
- Data analysts
- Data scientists
- Business analysts
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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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.
