1. A Ph. D Course on Recursive Partitioning Algorithms
2. A Semester on Probabilistic Models, Inference and Optimization for Engineers in Computer Science and Information Technologies
3. A Semester on Probability Theory for Engineers in Computer Science
4. A Semester on Statistics for Engineers in Computer Science
5. Instructor in Foundations of Problability Theory, Introduction to Mathematical Statistics and Inference and Advanced Probability Theory.
6. Seminars and trainings concerning Data Mining Techniques for private institutions and consulting companies. Topics include:

• An introduction to data mining

• Data mining with decision trees

• CART technology. A data mining tool

• Ensemble methods for pattern analysis

• Random Forests technology

• Hot topics in boosting. TreeNet technology

• Data mining with neural networks

• An introduction to support vector machines

• Dimension reduction techniques

• An introduction to cluster analysis

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MS. STUDENTS

• Aitor Gutiérrez Fajardo. 2010. Statistical learning with support vector machines and kernel methods. Foundations and Applications (in spanish)

• José Ignacio Ezquerra. 2009. An introduction to the Boosting methodology for statistical learning (in spanish)