Data Science without Coding hassle: Introducing Rapidminer

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.