The course illustrates the basic concepts of Business Analytics with particular reference to the approaches for statistical data modeling, diagnostic and predictive analytics, using methodologies based on machine learning for the solution of application problems and decision support in industrial, management and economics fields.
The course introduces the basic concepts of Business Intelligence (BI) with particular reference to aspects of Analytics/Data Mining and focusing on the use analytical methods and reporting to support business decisions. The students will acquire both the basic skills for the design of a BI system and the ability to critically evaluate the data analysis performed with Data Mining tools. During the course some seminars are planned that illustrate real cases of application of the BI in the enterprise.
Basic knowledge of probability, statistics, analysis and data representation. Basic knowledge of Python or a similar programming language.
Lectures and computer assisted lab sessions.
Review of multivariate statistics and elements of decision theory Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics Supervised and unsupervised models Association Pattern Mining Cluster Analysis Rule-based methods and decision trees Kernel-based methods Elemsnts of neural networks Elements of methods for structured and semi-structured data Mehods for model evaluation Applications and case studies
Lecture notes provided during the course.
Further readings:
C.C.Aggarwal, Data mining: the textbook. Springer, 2015.
M.J.Zaki, M.Wagner Jr., Data Mining and Machine Learning: Fundamental Concepts and Algorithms. Cambridge University Press, 2019.
T.Hastie, R.Tibshirani, J.Friedman, The Elemsnts of Statistical Learning, Springer, 2009 (2nd Ed.)
Ricevimento: By appointment.
DAVIDE ANGUITA (President)
LUCA DEMETRIO
LUCA ONETO
Oral examination. The student will develop autonomously (individually or in cooperation with other students) a case study, selected among those proposed as exam topics and using the methods discussed during the course. The oral examination will focus on the discussion of the case study.
