Survival Data Mining: A Programming Approach
Business Knowledge Series course
This advanced course discusses predictive hazard modeling for customer history data. Designed for data analysts, the course uses SAS/STAT software to illustrate various survival data mining methods and their practical implementation.
Note: Formerly titled Survival Data Mining: Predictive Hazard Modeling for Customer History Data, this course now includes hands-on exercises so that you can practice the techniques that you learn. Other additions include a chapter on recurrent events, new features in SAS/STAT software, and an expanded section that compares discrete time approach versus the continuous time models such as Cox Proportional Hazards models and fully parametric models such as Weibull.
Learn how to
Who should attend
Before attending this course, you should
Many of the SAS examples use DATA step, macro, and SQL programming. The Predictive Modeling Using Logistic Regression and Survival Analysis Using the Proportional Hazards Model courses provide relevant background information. Prior attendance in these courses is advantageous but not required.
Survival Data Mining
|Dates||Location||Time||Language||Fee||Add to Cart|
|14-16,21-23 FEB 2018||Live Web||01:00 PM-04:30 PM EST||English||2475 USD / 5.1 EPTO|
|25-27 APR 2018 Connected Class||Live Web||09:00 AM-05:00 PM EDT||English||2475 USD / 5.1 EPTO|
|25-27 APR 2018||Arlington, VA||09:00 AM-05:00 PM EDT||English||2475 USD / 5.1 EPTO|
|30 MAY-01 JUN,04-06 JUN 2018||Live Web||01:00 PM-04:30 PM EDT||English||2475 USD / 5.1 EPTO|
|09-11 OCT 2018||New York, NY||09:00 AM-05:00 PM EDT||English||2475 USD / 5.1 EPTO|