Data Science and Economics - (Classe LM-91)-Enrolled from 2018/2019 Academic Year
Master programme
A.Y. 2019/2020
LM-91 - Tecniche e metodi per la societa dell'informazione (EN)
Graduates of this MSc program will receive advanced training on methodologies and IT tools, quantitative and methodological notions, to interpret and analyze economic phenomena using approaches that integrate business, market and social media data. Among these, the analysis of the effects of policies (economic, social) or the evaluation of actions (investments, marketing campaigns) and any other activity related to the sectors of economy, marketing, business and finance or social sciences.
The course of study provides for the construction of solid methodological bases through the development of topics of economic theory, decision theory under uncertainty conditions, micro-econometric techniques and analysis of time series. It also provides for the study of new data management technologies and scalability of analysis systems in cloud environments, as well as machine learning techniques for the extraction and classification of information.
After these compulsory basic training activities, the course of study specializes through the possibility of choosing courses for a total of 18 credits among different study paths suggested to students in the context of their autonomy and natural inclination. A first specialization course offers useful tools for economic applications in the area of policy or investment assessment, the study of production processes and the evolution of social phenomena, as well as the basis for new approaches to the analysis of financial markets and risk. A further focus is instead on the aspects of technological innovation and their impact on the data-driven business, including new markets and the fintech sector. A third address instead lays the foundations for the study of social phenomena through innovative technologies and techniques of social media analysis and textual analysis.
These specialization activities are geared, together with the external training activity, to the preparation of the thesis dissertation and to the final exam. Therefore, the thesis is considered as the fulfillment of a course of study and apprenticeship that originates in the choice of courses of address.
The courses of the degree course, both compulsory and those chosen, include lectures and laboratory classes as well as autonomous project activities and individual activities in the laboratory for not less than 10 total credits, in order to guarantee students an adequate preparation also from a practical point of view, in close contact with real data and specific case studies.
The in-depth studies in mathematics, statistics, information technology and economics, highly qualify the Data Science and Economics training project and prepares the students also for selective procedures of PhD and research programs in the areas of Data Science, Computer Science, Business Intelligence and Economics.
The course of study provides for the construction of solid methodological bases through the development of topics of economic theory, decision theory under uncertainty conditions, micro-econometric techniques and analysis of time series. It also provides for the study of new data management technologies and scalability of analysis systems in cloud environments, as well as machine learning techniques for the extraction and classification of information.
After these compulsory basic training activities, the course of study specializes through the possibility of choosing courses for a total of 18 credits among different study paths suggested to students in the context of their autonomy and natural inclination. A first specialization course offers useful tools for economic applications in the area of policy or investment assessment, the study of production processes and the evolution of social phenomena, as well as the basis for new approaches to the analysis of financial markets and risk. A further focus is instead on the aspects of technological innovation and their impact on the data-driven business, including new markets and the fintech sector. A third address instead lays the foundations for the study of social phenomena through innovative technologies and techniques of social media analysis and textual analysis.
These specialization activities are geared, together with the external training activity, to the preparation of the thesis dissertation and to the final exam. Therefore, the thesis is considered as the fulfillment of a course of study and apprenticeship that originates in the choice of courses of address.
The courses of the degree course, both compulsory and those chosen, include lectures and laboratory classes as well as autonomous project activities and individual activities in the laboratory for not less than 10 total credits, in order to guarantee students an adequate preparation also from a practical point of view, in close contact with real data and specific case studies.
The in-depth studies in mathematics, statistics, information technology and economics, highly qualify the Data Science and Economics training project and prepares the students also for selective procedures of PhD and research programs in the areas of Data Science, Computer Science, Business Intelligence and Economics.
The MSc program in Data Science and Economics aims to train the following professional figures.
Profile: Data Scientist.
Functions: Its main functions are to analyze and elaborate forecasts on large data flows, identifying and applying the most appropriate software tools and statistical techniques for their elaboration; create sophisticated models for predictive data-driven analysis. Data Scientist knows the different contexts in which data emerge and can interact with experts from various disciplines.
Skills: Statistical analysis. Programming. Knowledge of software tools.
Outlets: small and medium-sized enterprises, startups and public administration.
Profile: Data Driven Economist.
Functions: its main functions are to frame problems of economic analysis in the context of data science by identifying data and technologies that can provide new keys for reading or evaluating economic and social phenomena.
Skills: Economic theory, statistical and computer techniques.
Outlets: large companies, public administration and international organizations.
Profile: Data-Driven Decision Maker.
Functions: the professions included in this category exercise managerial functions of high responsibility in private and public companies with an international vocation with a strong technological component within it, using data analysis to guide strategic and operational decisions.
Skills: baggage of theoretical knowledge of an economic-quantitative-IT nature to support organizational decisions and the development of economic institutions and companies.
Outlets: small and medium-sized enterprises, large companies, public administration.
Profile: Analyst of development projects or economic policies
Functions: the professions included in this category contribute to the formulation, monitoring and analysis of development projects or economic policies.
Skills: the baggage of theoretical and operational notions in the economy, in the business management strategy, and in the economic policies that govern them.
Outlets: They operate in private or public companies in industry, commerce, business services, personal and similar services and in international and / or governmental institutions.
Profile: Marketing Analytics Manager.
Functions: the professions included in this category exercise functions of identification and supervision of decision-making processes of an operative nature in direct coordination with the company's executive management.
Skills: baggage of theoretical knowledge of an economic-quantitative-IT nature to support organizational decisions and the development of economic institutions and companies.
Outlets: large companies.
Employment statistics (Almalaurea)
Profile: Data Scientist.
Functions: Its main functions are to analyze and elaborate forecasts on large data flows, identifying and applying the most appropriate software tools and statistical techniques for their elaboration; create sophisticated models for predictive data-driven analysis. Data Scientist knows the different contexts in which data emerge and can interact with experts from various disciplines.
Skills: Statistical analysis. Programming. Knowledge of software tools.
Outlets: small and medium-sized enterprises, startups and public administration.
Profile: Data Driven Economist.
Functions: its main functions are to frame problems of economic analysis in the context of data science by identifying data and technologies that can provide new keys for reading or evaluating economic and social phenomena.
Skills: Economic theory, statistical and computer techniques.
Outlets: large companies, public administration and international organizations.
Profile: Data-Driven Decision Maker.
Functions: the professions included in this category exercise managerial functions of high responsibility in private and public companies with an international vocation with a strong technological component within it, using data analysis to guide strategic and operational decisions.
Skills: baggage of theoretical knowledge of an economic-quantitative-IT nature to support organizational decisions and the development of economic institutions and companies.
Outlets: small and medium-sized enterprises, large companies, public administration.
Profile: Analyst of development projects or economic policies
Functions: the professions included in this category contribute to the formulation, monitoring and analysis of development projects or economic policies.
Skills: the baggage of theoretical and operational notions in the economy, in the business management strategy, and in the economic policies that govern them.
Outlets: They operate in private or public companies in industry, commerce, business services, personal and similar services and in international and / or governmental institutions.
Profile: Marketing Analytics Manager.
Functions: the professions included in this category exercise functions of identification and supervision of decision-making processes of an operative nature in direct coordination with the company's executive management.
Skills: baggage of theoretical knowledge of an economic-quantitative-IT nature to support organizational decisions and the development of economic institutions and companies.
Outlets: large companies.
Employment statistics (Almalaurea)
They can access the second cycle degree course in Data Science and Economics, graduates with a degree awarded in Italy (ex d. 270/04) of the following classes:
l-7 Ingegneria civile e ambientale
l-8 Ingegneria dell'informazione
l-9 Ingegneria industriale
l-16 Scienze dell'amministrazione e dell'organizzazione
l-18 Scienze dell'economia e della gestione aziendale
l-20 Scienze della comunicazione
l-30 Scienze e tecnologie fisiche
l-31 Scienze e tecnologie informatiche
l-32 Scienze e tecnologie per l'ambiente e la natura
l-33 Scienze economiche
l-35 Scienze matematiche
l-36 Scienze politiche e delle relazioni internazionali
l-37 Scienze sociali per la cooperazione, lo sviluppo e la pace
l-41 Statistica
and students with a degree awarded in Italy (ex dm 509/99) in the equivalent classes to those listed above.
A verification of the minimum access requirements is foreseen in the measure of:
● 12 CFUs in the area of computer science and mathematics, disciplinary sectors: MAT-01 - MAT-09, INF-01, ING-INF/05
● 12 CFUs in the area of economic and statistical sciences, subject areas: SECS-S/01, SECS-P/05, SECS-P/01, SECS-P/02, SECS-P/07, SECS-P/08
In particular, the preparation required for the computer and mathematics area includes: general mathematics, linear algebra, programming and basic computer science; for the economic-statistical area: inferential statistics, basic econometrics, basic microeconomics, basic macroeconomics and elements of business sciences.
The possession of linguistic skills at least at B2 level in the English language is a requirement for access. The language skills of the required level must be proven by presenting one of the proven international validity certificates of level B2 or by passing a B2 level test organized within the University.
The profile of students regarding the knowledge required for access, motivations and individual preparation will be assessed on the basis of the evaluation of the curricula and through a selection interview conducted in English and exclusively by electronic means. This verification will be carried out by a specific "Selection Commission" of teachers appointed by the Faculty Board.
The selection committee reserves the right to admit on the basis of the results of the interview only the students who do not fully verify one or more of the minimum access requirements due to discrepancies in the system of credits or academic qualifications or other objective reasons identified by the analysis of the material attached to the application form.
Students with a foreign qualification are also required to ascertain the basic requirements equivalent to the minimum requirements for students with an Italian qualification.
The master's degree program also reserves the right to evaluate the possible inclusion of a programmed number, determined from year to year by the competent academic bodies, after evaluation of the structural, instrumental and personnel resources available for the functioning of the same.
l-7 Ingegneria civile e ambientale
l-8 Ingegneria dell'informazione
l-9 Ingegneria industriale
l-16 Scienze dell'amministrazione e dell'organizzazione
l-18 Scienze dell'economia e della gestione aziendale
l-20 Scienze della comunicazione
l-30 Scienze e tecnologie fisiche
l-31 Scienze e tecnologie informatiche
l-32 Scienze e tecnologie per l'ambiente e la natura
l-33 Scienze economiche
l-35 Scienze matematiche
l-36 Scienze politiche e delle relazioni internazionali
l-37 Scienze sociali per la cooperazione, lo sviluppo e la pace
l-41 Statistica
and students with a degree awarded in Italy (ex dm 509/99) in the equivalent classes to those listed above.
A verification of the minimum access requirements is foreseen in the measure of:
● 12 CFUs in the area of computer science and mathematics, disciplinary sectors: MAT-01 - MAT-09, INF-01, ING-INF/05
● 12 CFUs in the area of economic and statistical sciences, subject areas: SECS-S/01, SECS-P/05, SECS-P/01, SECS-P/02, SECS-P/07, SECS-P/08
In particular, the preparation required for the computer and mathematics area includes: general mathematics, linear algebra, programming and basic computer science; for the economic-statistical area: inferential statistics, basic econometrics, basic microeconomics, basic macroeconomics and elements of business sciences.
The possession of linguistic skills at least at B2 level in the English language is a requirement for access. The language skills of the required level must be proven by presenting one of the proven international validity certificates of level B2 or by passing a B2 level test organized within the University.
The profile of students regarding the knowledge required for access, motivations and individual preparation will be assessed on the basis of the evaluation of the curricula and through a selection interview conducted in English and exclusively by electronic means. This verification will be carried out by a specific "Selection Commission" of teachers appointed by the Faculty Board.
The selection committee reserves the right to admit on the basis of the results of the interview only the students who do not fully verify one or more of the minimum access requirements due to discrepancies in the system of credits or academic qualifications or other objective reasons identified by the analysis of the material attached to the application form.
Students with a foreign qualification are also required to ascertain the basic requirements equivalent to the minimum requirements for students with an Italian qualification.
The master's degree program also reserves the right to evaluate the possible inclusion of a programmed number, determined from year to year by the competent academic bodies, after evaluation of the structural, instrumental and personnel resources available for the functioning of the same.
One of the most effective policies adopted by European Union in the last years has been the internationalization of higher education. The various Erasmus programmes that have been implemented since the nineties have greatly increased the mobility of European students.
Being a brand-new programme with an internationally oriented educational core strategy, DSE promotes a wide internationalization of their students, and therefore strongly encourages them to spend part of their studies abroad in Erasmus+ Programmes.
Erasmus+ provides opportunities to study, train, gain work experience and skills. Students can go abroad from 3 up to 12 months (including a complementary traineeship period, if planned), and may receive additional grants for studying or training. At the end of their foreign stay, students get full recognition of completed activities in terms of credits for their degree. Student mobility is carried out in the framework of prior "inter-institutional agreements" between the sending and receiving institutions.
Students can also join the traineeship programme (Placement), by going abroad from 2 up to 12 months, starting their traineeship from the first year of study. For a traineeship which is an integral part of the curriculum, the sending institution must give full academic recognition for the period spent abroad. For a traineeship that is not part of the curriculum of the student, the sending institution shall provide recognition at least by recording this period in the Diploma Supplement or, in the case of recent graduates, by providing a traineeship certificate. Traineeship may also be established with private and public companies, educational or research centers other than the hosting institution, especially in the field of finance.
DSE academic staff has strong relations with some important European universities, in particular in Germany, Belgium, France, Spain and the Netherlands, and is actively involved in research and education networks, so that students' activity abroad (including the development of the final dissertation) can be successfully supervised.
Being a brand-new programme with an internationally oriented educational core strategy, DSE promotes a wide internationalization of their students, and therefore strongly encourages them to spend part of their studies abroad in Erasmus+ Programmes.
Erasmus+ provides opportunities to study, train, gain work experience and skills. Students can go abroad from 3 up to 12 months (including a complementary traineeship period, if planned), and may receive additional grants for studying or training. At the end of their foreign stay, students get full recognition of completed activities in terms of credits for their degree. Student mobility is carried out in the framework of prior "inter-institutional agreements" between the sending and receiving institutions.
Students can also join the traineeship programme (Placement), by going abroad from 2 up to 12 months, starting their traineeship from the first year of study. For a traineeship which is an integral part of the curriculum, the sending institution must give full academic recognition for the period spent abroad. For a traineeship that is not part of the curriculum of the student, the sending institution shall provide recognition at least by recording this period in the Diploma Supplement or, in the case of recent graduates, by providing a traineeship certificate. Traineeship may also be established with private and public companies, educational or research centers other than the hosting institution, especially in the field of finance.
DSE academic staff has strong relations with some important European universities, in particular in Germany, Belgium, France, Spain and the Netherlands, and is actively involved in research and education networks, so that students' activity abroad (including the development of the final dissertation) can be successfully supervised.
No obligation
Courses list
Second semester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Machine Learning, Statistical Learning, Deep Learning and Artificial Intelligence | 12 | 80 | English | INF/01 SECS-S/01 |
First trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Graph Theory, Discrete Mathematics and Optimization | 12 | 80 | English | MAT/09 SECS-S/06 |
Second trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Advanced Microeconomics and Macroeconomics | 12 | 80 | English | SECS-P/01 |
| Coding for Data Science and Data Management | 12 | 80 | English | INF/01 SECS-S/01 |
| Micro-Econometrics, Causal Inference and Time Series Econometrics | 12 | 80 | English | SECS-P/05 SECS-S/01 |
Second semester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Algorithms for Massive Data, Cloud and Distributed Computing | 12 | 80 | English | INF/01 |
| Optional | ||||
| Knowledge Extraction and Information Retrieval | 6 | 40 | English | INF/01 |
First trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Cybersecurity and Privacy Preservation Techniques and Digital Security and Privacy | 6 | 40 | English | IUS/01 IUS/09 IUS/14 |
| Optional | ||||
| Advanced Multivariate Statistics | 6 | 40 | English | SECS-S/01 |
| Game Theory | 6 | 40 | English | SECS-P/01 |
| Global Firms and Market | 6 | 40 | English | SECS-P/08 |
| Marketing Analytics | 6 | 40 | English | SECS-P/08 |
| Portfolio Optimization | 6 | 40 | English | SECS-S/06 |
| Social Network Analysis | 6 | 40 | English | INF/01 |
Second trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Digital Business Strategies | 6 | 40 | English | SECS-P/07 |
| Digital Society | 6 | 40 | English | SPS/07 |
| Fintech Industry | 6 | 40 | English | SECS-P/11 |
| Intellectual Property for Business: Strategy and Analysis | 6 | 40 | English | SECS-P/10 |
| Numerical Methods for Finance | 6 | 40 | English | SECS-S/01 |
| Probabilistic Modeling | 6 | 40 | English | SECS-S/01 |
| Public Opinion Research | 6 | 40 | English | SPS/11 |
| Risk Management | 6 | 40 | English | SECS-S/06 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | INF/01 SECS-S/01 |
Third trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Patients' Needs and Healthcare Markets | 6 | 40 | English | SECS-P/01 |
| Project Managements and Innovation in the Era of Big Data | 6 | 40 | English | SECS-P/08 |
Open sessions
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Bayesian Analysis | 6 | 40 | English | SECS-S/01 |
| Communication Research | 6 | 40 | English | SPS/07 |
| Experimental Methods and Behavioural Economics | 6 | 40 | English | SECS-P/02 |
| Human Resource Management Via Workforce Analytics | 6 | 40 | English | SECS-P/10 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | SECS-P/03 |
| Open Data for New Business | 6 | 40 | English | SECS-P/08 |
| Quantum Finance | 6 | 40 | English | SECS-S/06 |
| Sampling Techniques for Big Data | 6 | 40 | English | SECS-S/01 |
| Scientific Data Visualization | 6 | 40 | English | INF/01 |
| Social Network Analysis for Business and Organization | 6 | 40 | English | SECS-P/08 |
Conclusive activities
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Final Exam | 9 | 0 | English | |
Optional activities and study plan rules
1 - ECONOMICS (Suggested Path)
(3 activities among the following, but not more than 2 among those marked by *)
(course not activated in 2019/2020 marked by §)
Total 18 credits/ects
(3 activities among the following, but not more than 2 among those marked by *)
(course not activated in 2019/2020 marked by §)
Total 18 credits/ects
| Courses or activities | Max ECTS | Total hours | Language | Lesson period | SSD |
|---|---|---|---|---|---|
| Advanced Multivariate Statistics | 6 | 40 | English | First trimester | SECS-S/01 |
| Bayesian Analysis | 6 | 40 | English | Open sessions | SECS-S/01 |
| Experimental Methods and Behavioural Economics | 6 | 40 | English | Open sessions | SECS-P/02 |
| Fintech Industry | 6 | 40 | English | Second trimester | SECS-P/11 |
| Game Theory | 6 | 40 | English | First trimester | SECS-P/01 |
| Global Firms and Market | 6 | 40 | English | First trimester | SECS-P/08 |
| Knowledge Extraction and Information Retrieval | 6 | 40 | English | Second semester | INF/01 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | Open sessions | SECS-P/03 |
| Numerical Methods for Finance | 6 | 40 | English | Second trimester | SECS-S/01 |
| Patients' Needs and Healthcare Markets | 6 | 40 | English | Third trimester | SECS-P/01 |
| Portfolio Optimization | 6 | 40 | English | First trimester | SECS-S/06 |
| Probabilistic Modeling | 6 | 40 | English | Second trimester | SECS-S/01 |
| Quantum Finance | 6 | 40 | English | Open sessions | SECS-S/06 |
| Risk Management | 6 | 40 | English | Second trimester | SECS-S/06 |
| Sampling Techniques for Big Data | 6 | 40 | English | Open sessions | SECS-S/01 |
| Scientific Data Visualization | 6 | 40 | English | Open sessions | INF/01 |
2 - BUSINESS INNOVATION (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
(3 activities among the following)
Total 18 credits/ects
| Courses or activities | Max ECTS | Total hours | Language | Lesson period | SSD |
|---|---|---|---|---|---|
| Advanced Multivariate Statistics | 6 | 40 | English | First trimester | SECS-S/01 |
| Digital Business Strategies | 6 | 40 | English | Second trimester | SECS-P/07 |
| Fintech Industry | 6 | 40 | English | Second trimester | SECS-P/11 |
| Human Resource Management Via Workforce Analytics | 6 | 40 | English | Open sessions | SECS-P/10 |
| Intellectual Property for Business: Strategy and Analysis | 6 | 40 | English | Second trimester | SECS-P/10 |
| Knowledge Extraction and Information Retrieval | 6 | 40 | English | Second semester | INF/01 |
| Marketing Analytics | 6 | 40 | English | First trimester | SECS-P/08 |
| Open Data for New Business | 6 | 40 | English | Open sessions | SECS-P/08 |
| Probabilistic Modeling | 6 | 40 | English | Second trimester | SECS-S/01 |
| Project Managements and Innovation in the Era of Big Data | 6 | 40 | English | Third trimester | SECS-P/08 |
| Sampling Techniques for Big Data | 6 | 40 | English | Open sessions | SECS-S/01 |
| Scientific Data Visualization | 6 | 40 | English | Open sessions | INF/01 |
| Social Network Analysis for Business and Organization | 6 | 40 | English | Open sessions | SECS-P/08 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | Second trimester | INF/01 SECS-S/01 |
3 - SOCIAL SCIENCE (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
(3 activities among the following)
Total 18 credits/ects
| Courses or activities | Max ECTS | Total hours | Language | Lesson period | SSD |
|---|---|---|---|---|---|
| Advanced Multivariate Statistics | 6 | 40 | English | First trimester | SECS-S/01 |
| Communication Research | 6 | 40 | English | Open sessions | SPS/07 |
| Digital Society | 6 | 40 | English | Second trimester | SPS/07 |
| Game Theory | 6 | 40 | English | First trimester | SECS-P/01 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | Open sessions | SECS-P/03 |
| Patients' Needs and Healthcare Markets | 6 | 40 | English | Third trimester | SECS-P/01 |
| Probabilistic Modeling | 6 | 40 | English | Second trimester | SECS-S/01 |
| Public Opinion Research | 6 | 40 | English | Second trimester | SPS/11 |
| Sampling Techniques for Big Data | 6 | 40 | English | Open sessions | SECS-S/01 |
| Scientific Data Visualization | 6 | 40 | English | Open sessions | INF/01 |
| Social Network Analysis | 6 | 40 | English | First trimester | INF/01 |
| Social Network Analysis for Business and Organization | 6 | 40 | English | Open sessions | SECS-P/08 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | Second trimester | INF/01 SECS-S/01 |
Third trimester
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Laboratory "personalized Health Care" | 3 | 20 | Italian | MED/01 |
Conclusive activities
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | Max ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Internship/stage | 3 | 0 | English | |
Optional activities and study plan rules
4 - Students must earn 12 credits for elective activities.
Course location
Milano
Presidente del Collegio Didattico
Prof.ssa Silvia Salini
Tutors professors
Reference structures
Contacts
- Degree Course E-mail
[email protected] - Facebook
http://www.facebook.com/dseunimi - Twitter
https://twitter.com/DseUnimi - Stage Contact Person
Prof. Giancarlo Manzi e Prof.ssa Sabrina Gaito
A.Y. 2022/2023
A.Y. 2021/2022
A.Y. 2020/2021
A.Y. 2019/2020
Official documents