Course Structure

The Master degree in Data Science and Economics is a genuinely multidisciplinary programme, offering a well-balanced set of courses in data science and economics supported by several other courses. Students must acquire 120 ECTS to complete the programme; among them, 24 credits are devoted to additional educational and research activities, for example dissertation writing, research seminars and elective courses.

The following are mandatory for all students:

First year courses

Course ECTS Area Term
Advanced Microeconomics and Macroeconomics 12 Economics II+III
Coding for Data Science and Data Management 12 Informatics/Statistics II+III
Graph Theory, Discrete Mathematics and Optimization 12
Mathematical methods
of economics, finance
and actuarial sciences/
Operation research
I
Machine Learning, Statistical Learning, Deep Learning and Artificial Intelligence 12 Statistics/Informatics II+III
Micro-econometrics, Causal Inference and Time Series Econometrics 12 Econometrics/Statistics I+II
Total number of credits earned at the end of the first year 60

 

Second year courses

Course ECTS Area Term
Algorithms for Massive Data, Cloud and Distributed Computing 12 Informatics TO BE
DEFINED
Cybersecurity and privacy, Preservation Tecniques and Digital Security and Privacy 6 Private law/
Public law/
EU law
II
Cumulative number of credits earned after the second year’s mandatory courses 78

 

Choose your specialization path

At the end of the first year, students have to choose among one of the three curricula called Economics, Business Innovation and Social Science.

 

Curriculum: Economics

(3 activities among the following, but not more than 2 among those marked by *) Total 18 credits/ects

Course ECTS Area Term
Clustering and Probabilistic Modelling  6 Informatics TO BE
DEFINED
Datamining and Computational Statistics  6 Statistics TO BE
DEFINED
Economics of Government and Policy Evaluation*  6 Public economics TO BE
DEFINED
Experimental Methods and Behavioural Economics  6 Economic policy TO BE
DEFINED
Game Theory  6 Economics TO BE
DEFINED
Global Firms and Market  6 Economics TO BE
DEFINED
Industrial Organization and Competitive Policies  6 Economics TO BE
DEFINED
Knowledge Extraction and Information Retrieval  6 Informatics TO BE
DEFINED
Labour Economics and Policy Evaluation  6 Economics TO BE
DEFINED
Mathematical Methods for Finance*  6 Mathematical methods
of economics, finance
and actuarial sciences
TO BE
DEFINED
Numerical Methods for Finance  6 Statistics TO BE
DEFINED
Patients’ Needs and Healthcare Markets*  6 Public economics TO BE
DEFINED
Portfolio Optimization*  6 Mathematical methods
of economics, finance
and actuarial sciences
TO BE
DEFINED
Quantum Finance*  6 Mathematical methods
of economics, finance
and actuarial sciences
TO BE
DEFINED
Risk Management*  6 Mathematical methods
of economics, finance
and actuarial sciences
TO BE
DEFINED
Social Network Analysis  6 Informatics TO BE
DEFINED
Statistical Methods for Finance  6 Statistics TO BE
DEFINED
Text Mining and Sentiment Analysis  6 Informatics TO BE
DEFINED
Cumulative number of credits earned under curriculum Economics 96

 

Curriculum: Business Innovation

(3 activities among the following) Total 18 credits/ects

Course ECTS Area Term
Digital Business Strategies  6 Business administration and accounting studies TO BE
DEFINED
Fintech Industry  6 Financial markets and institutions TO BE
DEFINED
Human Resource Management Via Workforce Analytics  6 Organization and human resource
management
TO BE
DEFINED
Intellectual Property for Business: Strategy and Analysis  6 Management TO BE
DEFINED
Marketing Analytics  6 Management TO BE
DEFINED
Open Data for New Business  6 Management TO BE
DEFINED
Project Managements and Innovation in the Era of Big Data  6 Management TO BE
DEFINED
Social Network Analysis for Business and Organization 6 Organization and human resource
management
TO BE
DEFINED
Cumulative number of credits earned under curriculum Business Innovation
96

 

Curriculum: Social Science

(3 activities among the following) Total 18 credits/ects

Course ECTS Area Term
Clustering and Probabilistic Modelling  6 Informatics TO BE
DEFINED
Communication Research  6 General sociology TO BE
DEFINED
Datamining and Computational Statistics  6 Statistics TO BE
DEFINED
Game Theory  6 Economics TO BE
DEFINED
Knowledge Extraction and Information Retrieval  6 Informatics TO BE
DEFINED
Polimetrics  6 Political science TO BE
DEFINED
Public Opinion Analysis  6 Political sociology TO BE
DEFINED
Social Network Analysis  6 Informatics TO BE
DEFINED
Text Mining and Sentiment Analysis  6 Informatics TO BE
DEFINED
Cumulative number of credits earned under curriculum Social Science
96

 

Other activities for the completion of study program

To complete the study program the students have to choose additional elective course(s) or Laboratories for a total amount of 12 ECTS.

 

Master thesis & Stage

For the preparation of the final Master thesis, the students will earn 9 ECTS .
Moreover, DSE students will have to complete a  mandatory stage/internship equivalent to 3 ECTS.
The Master thesis might (and strongly suggested to) be related to the stage project.

 

The total number of credits at the end of the study program is 120 ECTS.

 

COURSE PROGRESSION REQUIREMENTS: none

 

Where to find details about each individual course?

You need to navigate the school website starting from this page.
The syllabus of each course can be found by clicking on “structure”.
In the “structure” page you can also find general information about the exams and the erogation period of the course.