Data Mining and Computational Statistics

A.Y. 2017/2018
9
Max ECTS
60
Overall hours
SSD
SECS-S/01
Language
English
Learning objectives
Course objectives are:
· To introduce students to the expanding world of big data analysis.
· To introduce students to basic concepts, techniques and applications of computational statistics & data mining to be used in finance and economics.
· To develop skills for using the R software in order to solve practical problems
· To achieve skills for doing independent study and research.
Expected learning outcomes
Undefined
Course syllabus and organization

Single session

Responsible
Lesson period
Second trimester
SECS-S/01 - STATISTICS - University credits: 9
Lessons: 60 hours
Professor: Manzi Giancarlo
Professor(s)
Reception:
Wednesday 2.30PM-5.30PM (appointment suggested, via Teams).
Room 37, 3rd Floor (due to sanitary emergency office hours in person are suspended - Office hours will be held via Teams)