Knowledge Discovery in Databases (KDD) Training in Cologne
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 Cologne or in NobleProg corporate training centers in Cologne.
Our training facilities are located at Theodor-Heuss-Ring 23 in Cologne. Located in a ...
Overview
Our training facilities are located at Theodor-Heuss-Ring 23 in Cologne. Located in a modern office building, our premises offer enough space for successful training courses centrally in Cologne, within walking distance of the underground station Ebertplatz.
Arrival
The NobleProg training facilities are located on the left bank of the Rhine, easily accessible from Cologne Central Station via underground lines 16 and 18. The building has a limited number of parking spaces.
Parking
Cars can be parked in the area along the Torstrasse and the nearby side streets, even if you may have to search for a moment. There is no charge for parking.
Local Services
In the area of Cologne's old town there are numerous localities and around the Cologne Cathedral, the landmark of the city, there are numerous hotels.
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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