Price: 4.00 USD | Size: 2.30 GB | Duration : 2.49 Hours | 21 Video Lessons | ENGLISH | INSTANT DOWNLOAD
Data Science with KNIME , How to do data cleaning with KNIME, AI Machine learning with KNIME, ETL with KNIME, data prep
 
KNIME for Data Science and Data Cleaning Video Training Online Course DOWNLOAD
 
What you'll learn
 
How to use Tensorflow in KNIME
How to do DataScience in KNIME WITH AND WITHOUT CODING
How to solve data cleaning and data preparation challenges
How to replace Excel and start KNIME for ETL and data cleaning issues
Examples of data science machine learning workflows with KNIME
Hopefully a higher efficiency in data preparation and data science related work
Enhance your basic KNIME skills already acquired 
 
Requirements
 
No extra costs - KNIME can be downloaded for free
Basic knowledge of machine learning is certainly helpful for the later lectures in this course
The course complements my other Data science course with KNIME on udemy (I try to keep the overlapp as little as possible to give you the best kind of experience)
Description
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).
 
Meet KNIME
 
 
 
 
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 completely free!
 
 
 
So, is it worth it to dive deeper into KNIME? ABSOLUTELY!
 
 
 
This course is the third KNIME class and expands the knowledge you have acquired in the other classes
 
"KNIME - a crash course for beginners"
 
"Data science and Data preparation with KNIME"
 
 
 
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 highly recommend to check at least the crash course first (which covers all the basics in a great and funny case study!)
 
In this class we extend our skills by
 
learning to use additional helpful KNIME nodes not covered in the other two classes
 
solve data cleaning challenges together
 
use pretrained models in tensorflow in KNIME (involves Python coding)
 
learn the fundametals for NLP tasks (Natural language processing) in KNIME using only KNIME nodes (without any additional coding)
 
If that does not sound like fun, then what? So, if that is interesting to you then let’s get started!
 
Are you ready? 
 
Who this course is for:
(Aspiring) data scientists
(Aspiring) data analysts
Everyone interested in the data analysis , data analytics and data science area
data scientists / analysts who want to work smarter faster and more efficient
Excel users who want to learn better ways to prepare data. Excel is nice but KNIME is AWESOME!
 
This course Content
 
KNIME A Guide for Absolute Beginners
 
Name
1 - Welcome and Introduction
2 - Let Us Get Started with KNIME - the Interface
3 - Let Us Take a Look at Our Case Study Data
4 - Reading Data into KNIME - the Basics.
5 - Using Loops for Data Import - How to Be More Efficient in KNIME
6 - Data Cleaning and Saving Files with KNIME
7 - Webscraping in KNIME - Extracting Currency Exchange Rates from an API
8 - Joining and Cleaning Our Data in KNIME
9 - Final Data Cleaning and Preparation Steps for Visualizing Our Results
10 - Bonus - Saving the Data as a Hyper Format for Tableau
11 - Visualization - an Introduction on How to Visualize in Tableau or Power BI
12 - Predictive Analytics in KNIME - Machine Learning AI to Predict Customer Churn
13 - KNIME - Log Out and Final Words
 
KNIME for Data Science and Data Cleaning
 
 
01.01-welcome to knime
01.02-copying or moving files with knime
01.03-reading multiple excel files-potential errors and solutions
01.04-reading multiple excel files-benefits of loops
01.05-excel files with different table structures in knime
01.06-useful nodes-column aggregations
01.07-countries-data cleaning challenge
01.08-merge table challenge in knime
01.09-a json file challenge in knime
01.10-create the neural network h5 model file to be used in knime
01.11-mismatching addresses-introduction to similarity search in knime
01.12-tensorflow neural network regression implementation in knime
01.13-transfer learning in knime using python scripts
01.14-introduction to nlp in knime part 1
01.15-nlp in knime part 2-data preprocessing and cleaning
01.16-nlp in knime part 3-bag of words and document vector
01.17-nlp in knime-choose ml algorithm and score our model
01.18-congratulations
02.01-copying or moving files with knime
02.02-reading multiple excel files-benefits of loops
02.03-excel files with different table structure in knime
Code.zip