Knowledge Discovery in Databases (KDD) Training in Rennes
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 Rennes can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Rennes, City Center
Le Loft, 3, rue de Robien , Rennes, france, 35000
Subway Saint Anne
Parking Place Hoche
Bus 36 - 51 - 70 - 71 - 151ex
Training can also be organized on your premises in S...
Subway Saint Anne
Parking Place Hoche
Bus 36 - 51 - 70 - 71 - 151ex
Training can also be organized on your premises in Strasbourg or remotely. The 3rd option is to rent a room specifically for the duration of the course.
Training sessions can be given in English or French. For each session, we organize a coordination call with the trainer and participants to adapt the program to your expectations and level. Training includes theory, discussion, questions/answers and practical exercises.
Remote training is delivered via DaDesktop for training, a software package published by NobleProg that enables participants to have a workstation (VM) set up specifically for the training.
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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