Knowledge Discovery in Databases (KDD) Training in Bilbao
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) trainings in Bilbao can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Bilbao
NobleProg Bilbao, Street Bikendi Kalea 5, Bizcaya, spain, 48001
Bilbao is a municipality located in the north of Spain, capital of the province and historical territory of Vizcaya, in the a...
Bilbao is a municipality located in the north of Spain, capital of the province and historical territory of Vizcaya, in the autonomous community of the Basque Country. The town of Bilbao is the capital and unique locality of the municipality, with 345 141 inhabitants.
Today it is a thriving city of services, which is in a process of aesthetic, social and economic revitalization led by the symbolic Guggenheim Museum Bilbao.
In addition to its airport, Bilbao has a large and effective line of railways and buses that circulate throughout the municipality.
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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