Knowledge Discovery in Databases (KDD) Training in Cordoba
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. Onsite live Knowledge Discovery in Databases (KDD) training can be carried out locally on customer premises in Cordoba or in NobleProg corporate training centers in Cordoba.
NobleProg -- Your Local Training Provider
Còrdoba - Ecipsa Tower
Nueva Córdoba, Av. Hipólito Yrigoyen, Cordoba, Argentina
Ecipsa Tower is a AAA office building, based on an avant-garde project and built on one of the corners of the renowned Nueva ...
Ecipsa Tower is a AAA office building, based on an avant-garde project and built on one of the corners of the renowned Nueva Córdoba neighborhood of the City and Province of the same name. Ecipsa Tower has a novel stylistic image from the construction of a state-of-the-art tower that emerges from a turn-of-the-century building whose façade has been fully preserved.
It is located in front of the Archbishopric of the city of Córdoba, at the corner of Av. Hipólito Yrigoyen and Obispo Trejo, in the Nueva Córdoba neighborhood.
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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