Claudio Sartori is Full Professor of Information Processing Systems at the Department of Computer Science and Engineering of the University of Bologna. He carries out research in the areas of machine learning, data mining, big data, distributed data bases and systems since 1983 and has been teaching in these areas since 1990. He is author of over 100 publications mainly in the international sphere, and he has participated in European research projects related to the industrial world.
Modern manufacturing processes exploit massively the digital technology, as is witnessed by the increasing interest towards the new operating paradigms known as “Industry 4.0”. The purpose of this module is to exploit the skills acquired in other modules, mainly “Data analysis”, “Data Mining” and “Operation Analytics”, to deal with the “Manufacturing data” and to extract information useful for increasing the effectiveness of manufacturing.
Models and methods for knowledge extraction from databases. Study of different types of data and methods of pre-treatment. The functions of Data Mining. Supervised and unsupervised learning. Algorithms and methods for constructing classification models. Clustering algorithms. Algorithms for discovering association rules. Methods for evaluating the quality of data mining results. Data mining laboratory in order to apply the studied methods.
Data Science and Business Analytics
Introduction to the base principles and methods of Data Mining and Machine Learning, with particular reference to Classification, Clustering, Association Rules. Analysis of the major problems related to data quality and data transformation. Use of open source software to solve data mining and machine learning problems, with specific reference to datasets related to environment and sustainability