Data Mining With R

label Diverse autorenew 2025-09-29, 17:01 history_edu Cristian Ion
The aim of this course is to teach the basic concepts of Data Mining. Reliability, regression, discrimination, clustiring and association anaylsis. The course covers both the theoritical and the implementation aspect of the topic and includes R program education and datamining case studies for R solutions. The goal is to educate students to a level whşch they can implement datat mining for their future research.

Period
25-08-2014 - 30-08-2014 (1 weeks)

Target group
Course targets; students (usually master and PhD) with basic statistical knowledge and researchers in the social science area; political science, sociology, business, psycology, economics, marketing, social work and also computer sciences, machine leraning and quantitative methods etc. who would like to learn and implement data mining. The course targets also the non academic participants who are working for government, NGO's, research companies, who would like to use Data Mining efficiently for their work purposses like, CRM, information management.

Course aim
The course aims to introduce Data Mining, with the scope, Classification and regression tasks, reliability estimations, Clustering methods, data evaluation after data mining process. The implementations will be done with hands on R examples and the expectation is that, at the end of the course, participants will be able successfully to conduct Data Mining using R, as well as be prepared to pursue self-directed study in the area.



Credits
0.0 ECTS creditsThe credit information will be announced later. For that please contact the ISTQL committee or check ISTQL website.

Course fee
EUR 600[Convert to USD]Academic Participants Course fee for Participants from Academic Institutions is 600 till the early registration date (May 16th 2013) and after that 700. This fee only includes the course registration, course related documents and supplies and offical non-charged social calendar. Accomandation or transportation are NOT included. Please indicate the Institution status on your application forms EUR 800[Convert to USD]Non-academic Participants Course fee for Participants from non- Academic Institutions is 800 till the early registration date (May 16th 2013) and after that 900. This fee only includes the course registration, course related documents and supplies and offical non-charged social calendar. Accomandation or transportation are NOT included.

Course leader
Lus Torgo has a degree on Systems and Informatics Engineering (University of Minho, Portugal, 1989), and a Ph.D. on Computer Science (U Porto, 2000). He is an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the Uni

ISTQL
Address: Istanbul University School of Business Avcilar Campus
Postal code: 34320
City: Istanbul
Country: Turkey
Website: http://www.istql.com/
E-mail: istanbul.quantitative.lectures@gmail.com
Phone: +902124737070-18269