Advanced Data Analysis and Modeling
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EL CURSO ES PRESENCIAL Y SE IMPARTE EN MADRID
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”.
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.
Module 1 (1.5 ECTS)
Course 1: Regression (15 h), Practical sessions: SPSS
Course 2: Association rules (15 h), Practical sessions: Bioinformatic tools (see sample)
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 (see sample)
Course 6: Hidden Markov Models (15 h), Practical sessions:HTK (see sample)
Course 7: Neural networks (15 h), Practical sessions: MATLAB (see sample)
Course 8: Time series analysis (15 h), Practical sessions: MATLAB (see sample)
Module 3 (1.5 ECTS)
Course 9: Multivariate data analysis (15 h), Practical sessions: SPSS
Course 10: Supervised pattern recognition (15 h), Practical sessions: Weka (see sample)
Course 11: Expert systems (15 h), Practical sessions: CLIPS, Jess (see sample)
Course 12: Clustering (15 h), Practical sessions: Weka (see sample)
D. Carlos Óscar Sánchez Sorzano