Knowledge Discovery in Databases (KDD) Training in Busan
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 Busan can be carried out locally on customer premises or in NobleProg corporate training centers.
Busan Jungang-dong Centre is located on the 7th floor of PanOcean B/D in which many tenants are forwarding companies, shippin...
Busan Jungang-dong Centre is located on the 7th floor of PanOcean B/D in which many tenants are forwarding companies, shipping firms, and conglomerates like Hyundai marine, Woori bank, Shinhan investment, Joongang newspaper. Jungang-dong is one of the main business districts in Busan, so there are many foreign consulates, financial corporations, hotels, shipping companies, etc.
The building is situated with good visibility in the centre of the traditional CBD area in Busan,100 meters from Jungang subway, 5 minutes walk to Busan International Ferry Terminal, and 4 minutes drive to Busan KTX Station or Nampo-dong downtown area.
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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