Knowledge Discovery in Databases (KDD) Training in Hamburg
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. Hamburg onsite live Knowledge Discovery in Databases (KDD) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located in the Betahaus at Eifflerstraße 43 in Hamburg. E...
Overview
Our training facilities are located in the Betahaus at Eifflerstraße 43 in Hamburg. Easily accessible and centrally located in the Hanseatic city steeped in tradition, this is the ideal location for our participants.
Arrival
The NobleProg training facilities are located in the middle of the Schanzenviertel. The nearest bus stops are "Schulterblatt" for Metrobus line 15 and "Sternbrücke" for Metrobus line 3. The nearest S-Bahn and U-Bahn stations are Sternschanze.
Parking
In the area along the Eifflerstrasse and the nearby side streets, cars can be parked, even if you have to search for a moment. There is no charge for parking..
Local Services
The Schanzenviertel offers a wide range of gastronomic options and with Pyjama Park, Hotel Boston and other small and medium-sized hotels, local accommodation is also possible.
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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