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Data science and Data preparation with KNIME

KNIME - a powerful tool for data science and machine learning Data science with higher efficiency. KNIME data cleaning

4.58 / 5.0
987 students4 hours 20 minutes

Created by Dan We, offered on Udemy

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Course length


We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 4 hours 20 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.

Overall score


This course currently has a bestcourses score of 6.1/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.


Data science and Data cleaning and Data preparation with KNIME

Hello everyone hope you are doing fine.

Let’s face it. Data preparation ,data cleaning, data preprocessing (whatever you want to call it) is most often the most tedious and time consuming work in the data science / data analysis area.

So many people ask: How can we speed up the process and be more efficient?

Well one option could be to use tools which allow us to speed up the process (and sometimes reduce the amount of code we need to write).


A great tool which comes to our rescue. KNIME allows us to do data preparation / data cleaning in a very appealing drag and drop interface. (No coding experience is required yet it still allows us if we want to use languages like R, Python or Java. So, we can code if we want but don’t have to!). The flexibility of KNIME makes that happen. WITH KNIME we can also do Data Science, so machine learning and AI with or without coding.

And the best: The Desktop version is free!

So, is it worth it to dive deeper into KNIME? ABSOLUTELY!

This course is the second KNIME class and expands the knowledge you have acquired in the first class "KNIME - a crash course for beginners" which is  also available on udemy.

We do not cover the basics (e.g. the interface, basic data import and filter nodes,...) here. If you need  to refresh your knowlege or you have not had the chance to learn the basics I would recommend to check the prior class first (which covers all the basics in a great case study!)

In this class we dive into

  • efficient ways to import multiple files into KNIME

  • loops

  • webscraping

  • scripting (using Python code in KNIME)

  • hyperparameter optimization

  • feature selection

  • basic machine learning workflows and helpful nodes for this in KNIME

If that does not sound like fun, then what? So, if that is interesting to you then let’s get started!

Are you ready? 

What you will learn

  • New job opportunities might open up for you
  • You might be able to increase your productivity and save time in your data preparation tasks
  • Hopefully a higher efficiency in data preparation and data science related work
  • What kind of loops are available and how to use them in KNIME
  • Examples of data science machine learning workflows with KNIME
  • Enhance your basic KNIME skills already acquired ( for example in my KNIME crash course on udemy)
  • How to use Python in KNIME (Java and R could also be used but will not be the focus here)
  • How to do DataScience in KNIME WITH AND WITHOUT CODING


  • No extra costs - KNIME can be downloaded for free
  • You should have worked with KNIME before
  • The program itself and the basics are covered in "KNIME - a crash course for beginners" which is also available on udemy
  • Basic knowledge of machine learning is certainly helpful.
  • Coding is not required but we learn how you can use python and use your python code in KNIME
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Frequently asked questions

  • Price: $109.99
  • Platform: Udemy
  • Language: English
  • 4 hours 20 minutes
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bestcourses score: 6.1/10

There might be better courses available for this topic.