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Fundamentals of Data Mining and Predictive Analytics

7 Apr , 2018  

Requirements
  • No prerequisites. Course does not cover coding examples.
 
Description

A proper predictive analytics and data-mining project can involve many people and many weeks. There are also many potential errors to avoid. A “big picture” perspective is necessary to keep the project on track. 

This course provides that perspective where students will learn the basics of data mining and predictive analytics. Learn the steps of a real-world project, from defining the problem to putting the solution into practice, and review CRISP-DM and the 9 laws of data mining.

 We will walk through each step of a typical project, from defining the problem and gathering the data and resources, to putting the solution into practice. Keith also provides an overview of CRISP-DM (the de facto data-mining methodology) and the nine laws of data mining, which will keep you focused on strategy and business value.

Who is the target audience?
  • Data Scientists
  • Analytics Management
 
 
 
 
 

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