Summerschool on Advanced data analysis and modelling

Posted by on April 22, 2006, 3:16 pm

Dear colleagues,

San Pablo - CEU University in collaboration with other five
universities (M=E1laga, Polit=E9cnica de Madrid, Pa=EDs Vasco, Rey Juan
Carlos, and Castilla La Mancha), nine companies, CSIC and IEEE
organizes a summerschool on "Advanced Data Analysis and Modeling" in
Madrid between June 26th and July 27th. The full summerschool is 120
hours long and is divided into 10 courses. Attendees may register in
each course independently. The deadline for registration is June 1st.
For more information, please, visit
http://biocomp.cnb.csic.es/~coss/Docencia/ADAM/ADAM.htm

Best regards, Carlos Oscar

*List of courses and brief description* (full description at
http://biocomp.cnb.csic.es/~coss/Docencia/ADAM/ADAM.htm)

Course 1. STATISTICAL INFERENCE (June 26th - June 29th)
Introduction, Some basic statistical tests, Simple linear regression.
Practical sessions: SPSS
Course 2. MULTIVARIATE DATA ANALYSIS (June 26th - June 29th)
Introduction, Data examination, Factor analysis, MANOVA,
Multidimensional scaling, Structural equation modeling. Practical
sessions: SPSS
Course 3. BAYESIAN NETWORKS (July 3rd - July 6th)
Basics, Inference in Bayesian networks, Learning Bayesian networks from
data. Practical sessions: Hugin, Elvira, Weka, LibB
Course 4. NEURAL NETWORKS (July 3rd - July 6th)
Introduction, Perceptron networks, The Hebb rule, Multivariate
optimization, Rule of Widrow-Hoff, Backpropagation. Practical sessions:
MATLAB
Course 5. ASSOCIATION RULES (July 10th - July 13th)
Introduction, Rule discovering, Knowledge discoverage in biological
data, Applications. Practical sessions: Bioinformatics tools
Course 6. EXPERT SYSTEMS (July 10th - July 13th)
Introduction, Expert system programming, Hybrid systems. Practical
sessions: CLIPS and JESS
Course 7. HIDDEN MARKOV MODELS (July 17th - July 20th)
Introduction, Discrete HMM, Basic algorithms, Semicontinuous HMMs,
Continuous HMMs, Clustering, Generalized HMMs. Practical sessions: HTK
Course 8. TIME SERIES ANALYSIS (July 17th - July 20th)
Introduction. Probability models, Regression and Fourier analysis,
Forecasting and Data mining. Practical sessions: MATLAB, R.
Course 9. DATA MINING (July 24th - July 27th)
Introduction, Exploring data, Classification, Cluster analysis,
Survival analysis, Anomaly detection. Practical sessions: R, WEKA
Course 10. PATTERN RECOGNITION (July 24th - July 27th)
Introduction, Performance of supervised classification, Preprocessing,
k-nearest neighbor, classification trees, logistic regression, rule
induction, combining classifiers, unsupervised classification.
Practical sessions: WEKA

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