Knowledge Discovery in Databases (KDD) Training in Cancun
Online or onsite, instructor-led live Knowledge Discovery in Databases (KDD) training courses demonstrate through interactive hands-on practice the processes involved in KDD and how to implement those processes.
KDD training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Cancun onsite live Knowledge Discovery in Databases (KDD) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Cancun, Punta Cancun ICC
Cancun International Convention Center, Blvd. Kukulcan Km. 9, Cancun, mexico, 77500
Work in the heart of "Punta Cancún", the main business area of the city and within the International Convention Center, wher...
Work in the heart of "Punta Cancún", the main business area of the city and within the International Convention Center, where large events and business shows are held.
This modern business center is strategically located in a busy area, surrounded by banks, hotels, restaurants, shops and a wide variety of services.
Fully equipped offices, ready to start working when you enter
Business lounge to work while traveling
Easily booked meeting rooms
Regus IT High Speed Internet Access
Secure parking
Administrative support on request
Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing.
In this instructor-led, live course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes.
Audience
Data analysts or anyone interested in learning how to interpret data to solve problems
Format of the Course
After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.
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