Introduction to Predictive analytics: Business analytics types, applications, Analytical Techniques, Tools.

Predictive Modelling: Propensity Models, Cluster Models, Applications.

Modelling Techniques: Statistical Modelling, Machine Learning, Empirical Bayes Method, Point Estimation.

Data Pre-processing: Data Transformations for Individual Predictors, Data Transformation for Multiple Predictors, Dealing with Missing Values, Removing Predictors, Adding Predictors, Binning Predictors. Over-Fitting and Model Tuning.

Regression Models: Measuring Performance in Regression Models – Linear Regression and Its Cousins -Non-Linear Regression Models – Regression Trees and Rule-Based Models Case Study: Compressive Strength of Concrete Mixtures.

Classification Models: Measuring Performance in Classification Models – Discriminant Analysis and Other Linear Classification Models – Non-Linear Classification Models – Classification Trees and Rule-Based Models – Model Evaluation Techniques.