India |
- Title of the course: Certificate Course on Machine Intelligence and Soft Computing
- Level: Postgraduate
- Institute and departament: Center for Soft Computing Research, Indian Statistical Institute, Kolkata
- Short description of topics: Pattern recognition; Image processing; Fuzzy sets; Neural networks; Evolutionary computation; Project work on real life problems.
- Lecturer or responsible person: S. K. Pal
- Other people involved: A. Ghosh, D.P. Mandal, M.K. Kundu, C.A. Murthy, S. Mitra, B. Chanda, P. Maji, K. Ghosh
- Language: English
- Web page: http://www.isical.ac.in/~scc
- Starting year of the course in its present form: August 2007
- Goals/contents of the course: This is a value addition course for post graduate degree holders. The objective of the program is to train the students with the scientific knowledge in soft computing and machine learning paradigm. This may help the students for getting suitable job or accelerating research activities.
- Duration and period: 6-8 months.
- Approximate number of students: 20
- Additional information: Visit the website: http://www.isical.ac.in/~scc
or email qreries to: scc@isical.ac.in
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Taiwan, ROC |
- Title of the course: Fuzzy Set Theory and Applications
- Level: graduate
- Institute and departament: Industrial Engineering &Engineering Management, National Tsing Hua University
- Short description of topics: Introduction to the theories & logic of fuzzy sets with uncertainties in information and its uses in systems optimization and decision making.
- Lecturer or responsible person: Hsiao-Fan Wang
- Language: English
- Web page: http://softlab.ie.nthu.edu.tw
- Starting year of the course in its present form: Feb. 2010
- Goals/contents of the course: The main contents are:
1. Introduction and Review of Set Theory
2. Fuzzy Sets and Operations
3. Fuzzy Numbers and Arithmetic
4. Fuzzy Relations
5. Fuzzy Events and Fuzzy Regression
6. Fuzzy Measures
7. Fuzzy Linear Programming
8.*Fuzzy Decision Making
9. Fuzzy Clustering and Pattern Recognition
10Trend of softt Computing
- Slides or others supporting material: http://softlab.ie.nthu.edu.tw
- Duration and period: One semester
- Approximate number of students: 30
- Intended audience: Engineering and Management students
- The course is part of: master/phd in Industrial Engieering & Engineering Management
- Type: elective
- Additional information: a term project is required
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Spain |
- Title of the course: Master in Soft Computing and Intelligent Data Analysis
- Level: Master
- Institute and departament: European Centre for Soft Computing and Universtity of Oviedo
- Short description of topics: Soft computing, Fuzzy logic, Neural networks, Evolutionary computation, Meta-heuristics, Probabilistic reasoning, Intelligent data analysis, Hybrid systems, ...
- Lecturer or responsible person: Luis Magdalena
- Other people involved: More than forty lecturers including: P. Bonissone, C. Borgelt, J.L. Castro, O. Cordón, S. Crone, D. Dubois, B. Gabrys, M.A. Gil, F. Herrera, J. Kacprzyk, R. Kruse, M. Laguna, P. Larrañaga, R. López de Mántaras R. Martí, C. Moraga, A. Nürnberger, G. Pasi and E. Trillas
- Language: English
- Web page: http://www.softcomputing.es/master
- Starting year of the course in its present form: 2009
- Goals/contents of the course: The general objective of the Master program is to prepare students for highly qualified positions in a wide range of jobs in the public and the private sector,
and to provide students with the foundations required to pursue a PhD degree.
Its specific objective is to train researchers to make significant contributions to scientific knowledge in soft computing and intelligent data analysis environment.
- Duration and period: One year, full time
- Additional information: Visit the web http://www.softcomputing.es/master or e-mail your questions to master@softcomputing.es
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Italy |
- Title of the course: Problems and approaches in computational chemistry
- Level: graduate
- Institute and departament: Politecnico di Milano, DEI
- Short description of topics: Computational chemistry is a well developed intersection of chemistry and computer science that employs the results of theoretical chemistry to compute the structures and properties of molecules. Present computational chemistry can accurately calculate the properties of molecules that contain no more than 10-40 electrons. Approximate methods are available for larger molecules.
The course will introduce the methods used in the basic areas of computational chemistry:
1. The prediction of the molecular structure of molecules
2. Storing and searching for data on chemical entities
3. Identifying correlation between chemical structures and properties
4. Computational approaches to design molecules that interact in specific ways with other molecules (eg drug design)
After a review of the area we will present the open challenges.
Challenges in size: work with big molecules (proteins, etc), work on large data sets, etc.
Challenges in the meaning: classification of the chemical space, classification of the mechanisms space, etc.
Challenges in the perspectives: from "in vivo" testing to "in silico" testing.
Challenges in the hybridization with new areas: how proteomics, genetics, neurosciences can build over computational chemistry.
The course will be organized with the cooperation of external experts and problem holders.
- Lecturer or responsible person: Giuseppina Gini
- Other people involved: Emilio Benfenati (Mario Negri Institute, Milan)
- Language: English
- Web page: http://home.dei.polimi.it/gini/CompChem/
- Starting year of the course in its present form: 2008
- Goals/contents of the course: The goal is to introduce the students to the topic and to review with them relevant publications in the computer science and AI areas.
- Text book or classnotes: http://home.dei.polimi.it/gini/CompChem/lezioni.htm
- Slides or others supporting material: http://home.dei.polimi.it/gini/CompChem/
- Duration and period: 20 hours
- Approximate number of students: 25
- Intended audience: PhD student in ICT
- The course is part of: Doctorate in Information Technology at Politecnico di Milano
- Type: elective
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