This Survival Data Mining: A Programming Approach training course covers 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.
By attending Survival Data Mining: A Programming Approach workshop, delegates will learn to:
- Build models for time-dependent outcomes derived from customer event histories
- Account for competing risks, time-dependent covariates, right censoring, and left truncation
- Handle large data sets
- Compute the expected value of the remaining time until an event
- Evaluate the predictive performance of the model.
- Basic understanding of survival analysis
- Experience with predictive modeling, particularly with logistic regression
- Familiar with statistical concepts such as random variables, probability distributions, and parameter estimation
- Familiar with sql (including topics such as sub-queries and left-joining)
- SAS programming proficiency.
The Survival Data Mining: A Programming Approach class is ideal for:
- Predictive modelers, data analysts, statisticians, econometricians, model validators, and data scientists