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Certificate
Course Outline
Day 1:
Module 1: KNIME Analytics Platform: Overview
- Installation procedures.
- Launching and customising KNIME Analytics Platform.
- Understanding nodes, data, and workflows.
- The data science lifecycle.
Module 2: Data Access
- Reading data from files.
- Accessing REST Services.
Module 3: ETL and Data Manipulation
- Filtering rows and columns.
- Using aggregators.
- Joining and concatenating data.
- Transformation techniques: conversion, replacement, standardization, and feature engineering.
- Preparing data for time series analysis.
Day 2:
Module 4: Exporting Data
- Writing data to files.
- Creating reports.
Module 5: Data Visualization
- Interactive univariate visual exploration.
- Interactive multivariate visual exploration.
-
Advanced visualization features.
Module 6: Predictive Analytics using KNIME
- Fundamental data mining concepts.
- Regression techniques.
- The decision tree family.
- Model evaluation methods.
Day 3:
Module 7: Controlling the Flow
- Workflow parameterization using flow variables.
- Re-executing workflow segments using loops.
- Optimising and cleaning up your workflow.
Module 8: Practical KNIME Analytics Platform Case Study
Requirements
Recommended
- A foundational understanding of interpreting data.
- Experience with core data processing techniques.
Target Audience
- Data analysts.
- Data scientists.
- Business analysts.
21 Hours
Testimonials (2)
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.
Ian - Archeoworks Inc.
Course - ArcGIS Fundamentals
Radomir was very patient and helpful when I got stuck. He was very knowledgeable about the subject matter, and his explanations on different concepts were detailed and thorough.
