UNIPI
M.Sc. in Data Science and BI
Polo Fibonacci, University of Pisa
Dino PEDRESCHI
96
Y
The formidable advances in computing power, data acquisition, data storage and connectivity have created unprecedented amounts of data. Data mining, i.e., the science of extracting knowledge from these masses of data, has therefore been affirmed as an interdisciplinary branch of computer science.
Data mining techniques have been applied to many industrial, scientific, and social problems, and are believed to have an ever deeper impact on society. The course objective is to provide an introduction to the basic concepts of data mining and the process of extracting knowledge, with insights into analytical models and the most common algorithms.
Mining of time series and spatio-temporal data
Mining of sequential data and graphs
Advanced techniques for classification, clustering and outlier detection
Language, standard and architectures of data mining systems
Social impact of data mining
Data mining and privacy protection
Case studies in socio-economic domains (marketing and CRM, mobility and transport, public health, etc.)