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Certificate
Course Outline
Introduction
Getting Started with Knime
- What is KNIME?
- KNIME Analytics
- KNIME Server
Machine Learning
- Computational learning theory
- Computer algorithms for computational experience
Preparing the Development Environment
- Installing and configuring KNIME
KNIME Nodes
- Adding nodes
- Accessing and reading data
- Merging, splitting, and filtering data
- Grouping and pivoting data
- Cleaning data
Modeling
- Creating workflows
- Importing data
- Preparing data
- Visualizing data
- Creating a decision tree model
- Working with regression models
- Predicting data
- Comparing and matching data
Learning Techniques
- Working with random forest techniques
- Using polynomial regression
- Assigning classes
- Evaluating models
Summary and Conclusion
Requirements
- Experience with Python
- R experience
Audience
- Data Scientists
14 Hours
Testimonials (5)
it was informative and useful
Brenton - Lotterywest
Course - Building Web Applications in R with Shiny
Many examples and exercises related to the topic of the training.
Tomasz - Ministerstwo Zdrowia
Course - Advanced R Programming
Very useful in because it helps me understand what we can do with the data in our context. It will also help me
Nicolas NEMORIN - Adecco Groupe France
Course - KNIME Analytics Platform for BI
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
It was very informative and professionally held. Wojteks knowledge level was so advanced that he could basically answer any question and he was willing to put effort into fitting the training to my personal needs.
