Data Science without Coding hassle: Introducing Rapidminer
3.0 (11 ratings)
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Data Science without Coding hassle: Introducing Rapidminer

Rapidminer set up and getting started with data processing.
3.0 (11 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
26 students enrolled
Created by Sanya Chaudhary
Last updated 1/2017
English
Curiosity Sale
Current price: $10 Original price: $20 Discount: 50% off
30-Day Money-Back Guarantee
Includes:
  • 44 mins on-demand video
  • 1 Article
  • 5 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Install and set up Rapidminer predictive analytics platform.
  • Open different file formats like .csv and .xml.
  • Manipulate the dataset aka example set (a rapidminer lingo).
  • Make HTTP calls and manipulate the response to desired format.
  • Install Rapidminer extensions from marketplace.
  • Connect to PostgreSQL database using Rapidminer
View Curriculum
Requirements
  • Rapidminer is a drag n drop interface. Absolutely no coding experience is required. At the same time people with deep coding skills can utilize this course to a code-free world of Data Science.
  • At the same time people with deep coding skills can utilize this course to a code-free world of Data Science.
Description

Rapidminer, is #1 open source predictive analytics platform designed to accelerate predictive analytics in Big Data era. 

The processes in Rapidminer are set up as 'Drag n Drop" nodes, thus, absolutely no programming skills are required. Combined with FREE software access truly makes this a platform ideal to empower masses to participate in Data Science. Practically, any person with logical thinking and common day to day computer skills can break into the "elites" of Data Scientists! 

I will take you on a brief journey to introduce the Rapidminer Studio 6.3 suite and discuss its advantages over traditional data analytics platforms. Beginning with the download and setting up of the software, I will walk you through Rapidminer interface, different panels and views available for data analytics . All along the course, as we come across, I will explain Rapidminer lingo such as various Operators (nodes), Macros and debugging techniques etc. I will also show how to install additional extensions from marketplace.

To take you to the applied side of the house, we will set up a process to read XML files, traverse xml nodes using XPath property and the macro concept.
In the second exercise, I will share how to do a rather complicated work flow to make API calls and manipulate the response to extract and generate desired output. In the same workflow, I will demonstrate JSON to xml conversion and introduce some more operators (nodes) like Data to Documents, JSON to XML, Sub-process, Get Page, Get Pages and Write document etc.


By the end of the course, you will be able to:

  • Import data from different file formats like .csv and .xml.
  • Manipulate the imported data set aka example set (a Rapidminer lingo).
  • Make HTTP calls and manipulate the response to a desired format.
Who is the target audience?
  • Beginners
  • Entrepreneurs, C-level Executives, Managers
  • Anyone with an interest in Data Analytics including Non-Programmers
  • Programmers
  • No previous coding experience required.
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Curriculum For This Course
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Getting Started...
2 Lectures 12:39

What to expect in this course!

Also, I love feedback.. if you feel there is something specific you want to see please post comment or send me your question and I will submit new content here, if possible.

Preview 02:49

A course to help with installing Rapidminer and getting started, installing RM extensions from marketplace and interface walk through.


Preview 09:50
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Process XML
1 Lecture 08:59

How to parse XML file with Rapidminer.

The file attached is saved as .txt(due to some system limitation during upload). However, you can download and save this file with .xml and then use corresponding file with "Read XML" operator.

Set up Rapidminer workflow to open and parse XML documents.
08:59
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API calls with Rapidminer
1 Lecture 14:22

Github URL to try -- https://api.github.com/users/mralexgray/repos

Request Properties -- [ Content-Type = application/json ]

Make API calls and process the response
14:22

Refresher to the content reviewed.

Rapidminer Basics
3 questions
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Connect to PostgreSQL using Rapidminer
1 Lecture 08:16

Connect to SQL database using Rapidminer

Download PostgreSQL - https://www.postgresql.org/download/

Documentation on PostgreSQL, Getting started - https://www.postgresql.org/docs/9.3/static/index.html

Connect to PostgreSQL and fetch table data into Rapidminer Example set
08:16

PostgreSQL with Rapidminer
2 questions
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Yet to come - Connect Rapidminer with R and run Naive Bayes on the sample data
1 Lecture 00:03

Leverage the power of R with Rapidminer, 1+1=3!

Install Rapidminer Extension and setup with R framework on your PC/Laptop
00:03
About the Instructor
Sanya Chaudhary
3.0 Average rating
11 Reviews
26 Students
1 Course
Associate Director Analytics

I am a seasoned Data Scientist with more than a decade of programming, analytics and management expereince. My expertise comprise Big data Analytics using Rapidminer, R, Qlikview, Apache spark, Java.
In my day job, I work as Associate Director - Big Data Analytics and gets to interact with Managers and Business Intelligence professionals. I am very active in implementing Rapidminer based solutions in my enterprise. 
Since Rapidminer is an open source platform, I have designed from scratch several custom nodes for Rapidminer with backend in JAVA.  I feel there is a great potential for Rapidminer which is Big Data ready and that too by using simple and intuitive drag and drop methods. 


I love participating in Hackathons, hiking, and coaching school kids.