FINANCIAL DATA SCIENCE
Stampa
Enrollment year
2020/2021
Academic year
2021/2022
Regulations
DM270
Academic discipline
SECS-P/06 (APPLIED ECONOMICS)
Department
DEPARTMENT OF ELECTRICAL,COMPUTER AND BIOMEDICAL ENGINEERING
Course
COMPUTER ENGINEERING
Curriculum
Data Science
Year of study
Period
1st semester (27/09/2021 - 21/01/2022)
ECTS
6
Lesson hours
45 lesson hours
Language
English
Activity type
WRITTEN AND ORAL TEST
Teacher
RAFFINETTI EMANUELA (titolare) - 6 ECTS
Prerequisites
Statistics, Computer programming
Learning outcomes
Introduction to data science methods, software codes and applications to finance
Course contents
Linear regression, logistic regression, network models, neural networks, cluster, tree models, model comparison, financial technologies, applications of data science to finance
Teaching methods
Papers, R software codes, data
Reccomended or required readings
Handed out during the class.
Assessment methods
Written exam and discussion of a case study.
Further information
Sustainable development goals - Agenda 2030