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Second CEU Summerschool on Advanced Data Analysis and Modelling

Madrid, July 9th-27th, 2007
Universidad San Pablo CEU
Second CEU Summerschool on Advanced Data Analysis and Modelling
 
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Presentation

This summerschool is organized by the Polytechnical School of the Univ. San Pablo - CEU in a joint effort with a number of universities and companies: IEEE EMBS (Engineering in Medicine and Biology Society), SPSS, National Center of Biotechnology (CSIC), Univ. San Pablo – CEU, Univ. Complutense de Madrid, Univ. De Castilla La Mancha, Univ. De Málaga, Univ. Politécnica de Madrid, Univ. País Vasco. It is an intensive course (90 hours in 3 weeks) aiming at providing attendees with an introduction to the theoretical foundations as well as the practical applications of some of the modern statistical analysis techniques currently in use. The summerschool takes 3 weeks and is divided into 3 modules (each one with 4 subjects). Each subject has 8 theoretical classes and 7 practical classes in which each technique is put into practice with a computer program.  Students may register only in those courses of their interest.

Academic Interest: this course complements the background of many students from a variety of disciplines with the theoretical and practical fundamentals of those modern techniques employed in the analysis and modelling of large data sets. The academic interest of this course is high since there are no specific university studies on this kind of techniques.

Scientific interest: any scientist in most fields (engineering, life sciences, economics, etc.) is confronted to the problem of extracting conclusions from a set of experimental data. This course supplies experimentalists with the sufficient resources to be able to select the appropriate analysis technique and how to apply it to their specific problem.

Professional interest: the application of modern data analysis in the industry is well spread since it is practically needed in nearly all disciplines. As for job offers, it is a quite demanded topic: a search in Monster.com as for April 2006 retrieves more than 1000 offers for “data analysis”, more than 1000 offers for “data mining”, and 431 offers for “statistical consultant”.

 
Goals

The goals of this summer school are to complement the technical background of attendees in the field of data analysis and modelling. This course is open to any student or professional wanting to enlarge his knowledge of a topic that is more and more involved in nearly all productive areas (Computer Science, Engineering, Pharmacy, Medicine, Economics, Statistics, etc.)

A second objective of the summerschool is that the student is acquainted with a set of computational tools in which to try the techniques studied during the course on practical problems that they may bring on their own or that the summerschool professors may propose.

 
Programme

All classes will be given in English. Courses 1 and 2, 3 and 4, 5 and 6, ... are given simultaneously, therefore a student cannot register in two simultaneous courses.

 

Module 1 (1.5 ECTS)

Course 1: Regression (15 h), Practical sessions: SPSS

Course 2: Association rules (15 h), Practical sessions: Bioinformatic tools

Course 3: Statistical inference (15 h), Practical sessions: SPSS

Course 4: Dimensionality reduction (15 h), Practical sessions: SPSS

 

Module 2 (1.5 ECTS)

Course 5: Bayesian networks (15 h), Practical sessions: Hugin, Elvira, Weka, LibB

Course 6: Hidden Markov Models (15 h), Practical sessions:HTK

Course 7: Neural networks (15 h), Practical sessions: MATLAB

Course 8: Time series analysis (15 h), Practical sessions: MATLAB

 

Module 3  (1.5 ECTS)

Course 9: Multivariate data analysis (15 h), Practical sessions: MATLAB

Course 10: Supervised pattern recognition (15 h), Practical sessions: Weka

Course 11: Expert systems (15 h), Practical sessions: CLIPS, Jess

Course 12: Clustering (15 h), Practical sessions: Weka

 

 
Professors
 

Professor

Institution

Course

Schedule

Carlos Rivero Rodríguez Univ. Complutense Madrid

Regression

Morning
Oswaldo Trelles Salazar Univ. Málaga

Association rules

Morning
Jesús Bescos Sinde SPSS

Statistical inference

Afternoon
Alberto Pascual Montano Univ. Complutense Madrid

Dimensionality reduction

Afternoon
José Antonio Gámez
Pedro Larrañaga
Univ. Castilla-La Mancha
Univ. País Vasco

Bayesian networks

Morning
Ricardo de Córdoba Univ. Politécnica de Madrid

Hidden Markov Models

Morning
Luis Gavete
Lucía Gavete
Univ. Politécnica de Madrid

Neural networks

Afternoon
Carlos Óscar Sánchez Sorzano Univ. San Pablo CEU

Time series analysis

Afternoon
Carlos Óscar Sánchez Sorzano Univ. San Pablo CEU

Multivariate Data Analysis

Morning
Pedro Larrañaga Univ. País Vasco

Supervised pattern recognition

Morning
Carlos Iglesias Fernández Univ. Politécnica de Madrid

Expert systems

Afternoon
Carlos Óscar Sánchez Sorzano Univ. San Pablo CEU

Clustering

Afternoon


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