Knowledge Discovery in Databases (KDD) Training in Burnaby
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 Burnaby can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Burnaby - Metrotown
Suite 2600, 4720 Kingsway, Burnaby, Canada, V5H 4N2
The Burnaby Metrotown Centre is a 30-storey office building which is centrally located by Metrotown Sky train station and con...
The Burnaby Metrotown Centre is a 30-storey office building which is centrally located by Metrotown Sky train station and connected to the Metropolis shopping mall in Burnaby.
Burnaby Centre
Suite 200, 4170 Still Creek Drive , Burnaby , Canada, V5C 6C6
The Burnaby Centre is in a premier business park in North Burnaby. It is located close to Highway 1 and within walking distan...
The Burnaby Centre is in a premier business park in North Burnaby. It is located close to Highway 1 and within walking distance of Brentwood Town Centre and Gilmore SkyTrain Station.
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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