The list of topics includes, but is not limited to, the following:

A – Classification Theory
Bayesian Classification –Biplots – Clustering models – Consensus of Classifications – Correspondence Analysis – Discrimination and Classification – Factor Analysis and Dimension Reduction Methods – Fuzzy Methods –Genetic Algorithms –Hierarchical Classification – Multidimensional Scaling – Multiway Scaling – Multiway Methods – Neural Networks for Classification – Non Hierarchical Classification– Similarities and Dissimilarities –Software algorithms for classification – Unfolding and Related Scaling Methods

B –  Data Analysis
Bayesian data Analysis – Big data analysis- Categorical Data Analysis – Covariance Structure Analysis – Data Mining – Data Science –Data Visualization – Decision Trees – Functional data analysis – Mixture and Latent Class Models – Multilevel data Analysis – Non Linear Data Analysis – Nonparametric and Semiparametric Regression – Partial Least Squares – Pattern recognition – Robustness and Data Diagnostics – Social networks- Software algorithms for multivariate analysis – Spatial Data Analysis – Symbolic Data Analysis.