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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation process
- Launching and customizing KNIME Analytics Platform
- Nodes, data structures, 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
- Utilizing aggregators
- Joining and concatenating data
- Transformations: Conversion, Replacement, Standardization, and New Feature Generation
- Preparing data for time series analysis
Day 2:
Module 4: Exporting Data
- Writing data to files
- Generating reports
Module 5: Data Visualization
- Interactive univariate visual exploration
- Interactive multivariate visual exploration
-
Advanced visualization features
Module 6: Predictive Analytics using KNIME
- Foundational concepts in data mining
- Regression analysis
- Decision tree algorithms
- Model evaluation techniques
Day 3:
Module 7: Controlling the flow
- Workflow parameterization using flow variables
- Re-executing workflow segments via loops
- Organizing and cleaning up workflows
Module 8: Hands-on KNIME Analytics Platform based Case Study
Requirements
Recommended
- A foundational understanding of data interpretation.
- Familiarity with core data processing concepts.
Target Audience
- Data analysts
- Data scientists
- Business analysts
21 Hours
Testimonials (3)
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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.