Data science and economics (DSE) - No longer available
Data science and economics (DSE) - No longer available
Course sheet
A.Y. 2022/2023
Master programme
LM-91 - Methods and techniques for the information society
This programme has been terminated. Head to the new programme website to enrol in the first year.
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)
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.
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.
No obligation
Enrolment
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.
Candidates can prove their English language knowledge by presenting:
a certificate, at least level B2, of proven international validity (e.g., TOELF, IELTS, etc.);
a certificate attesting a B2 level test organized within the University;
a certification attesting a higher education qualification (bachelor) obtained in English;
a certification certifying the achievement of a university exam or English language qualification at least level B2, clearly stating the level achieved;
a certification attesting the achievement of at least 60 ECTS in teaching activities carried out in English during the university course in Italy or through international mobility programs.
Minimum curricular requirements cannot be considered as a verification of personal competencies and skills, which is mandatory. Admission is conditional on the assessment of the personal qualification by the Admission Board, whose member are appointed by the Faculty Board Collegio Didattico.
Assessment of personal competencies and skills is based on academic curriculum
(quality of the previous degree as well as the average grade obtained in the bachelor program. Grades obtained in mathematics, statistics, computer science and economics courses are also part of the evaluation) and choice coherence (coherence between the academic curriculum and/or activities previously carried out and the learning objectives of the MSc in Data Science and Economcis).
The Admission Board reserves the possibility to request the applicant an oral interview or written text for admission, held in English language and exclusively done via electronic devices (eg.: via skype or other platforms). The oral interview is aimed at verifying the individual preparation mentioned above. A complete detailed list of topics that may be requested during the interview is published on the website.
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.
Applicants must obtain the bachelor degree by 31st December 2021.
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.
Candidates can prove their English language knowledge by presenting:
a certificate, at least level B2, of proven international validity (e.g., TOELF, IELTS, etc.);
a certificate attesting a B2 level test organized within the University;
a certification attesting a higher education qualification (bachelor) obtained in English;
a certification certifying the achievement of a university exam or English language qualification at least level B2, clearly stating the level achieved;
a certification attesting the achievement of at least 60 ECTS in teaching activities carried out in English during the university course in Italy or through international mobility programs.
Minimum curricular requirements cannot be considered as a verification of personal competencies and skills, which is mandatory. Admission is conditional on the assessment of the personal qualification by the Admission Board, whose member are appointed by the Faculty Board Collegio Didattico.
Assessment of personal competencies and skills is based on academic curriculum
(quality of the previous degree as well as the average grade obtained in the bachelor program. Grades obtained in mathematics, statistics, computer science and economics courses are also part of the evaluation) and choice coherence (coherence between the academic curriculum and/or activities previously carried out and the learning objectives of the MSc in Data Science and Economcis).
The Admission Board reserves the possibility to request the applicant an oral interview or written text for admission, held in English language and exclusively done via electronic devices (eg.: via skype or other platforms). The oral interview is aimed at verifying the individual preparation mentioned above. A complete detailed list of topics that may be requested during the interview is published on the website.
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.
Applicants must obtain the bachelor degree by 31st December 2021.
This programme has been terminated. Head to the new programme website to enrol in the first year.
Programme description and courses list
course year not available
Open sessions
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Micro-Econometrics, Causal Inference and Time Series Econometrics | 12 | 80 | English | SECS-P/05 SECS-S/01 |
Not specified period
| Courses or activities | 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 |
| Graph Theory, Discrete Mathematics and Optimization | 12 | 80 | English | MAT/09 SECS-S/06 |
| Machine Learning, Statistical Learning, Deep Learning and Artificial Intelligence | 12 | 80 | English | INF/01 SECS-S/01 |
First trimester
| Courses or activities | 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 |
| Digital Society | 6 | 40 | English | SPS/07 |
| Fintech Industry | 6 | 40 | English | SECS-P/11 |
| Game Theory | 6 | 40 | English | SECS-P/01 |
| Global Firms and Market | 6 | 40 | English | SECS-P/08 |
| Intellectual Property for Business: Strategy and Analysis | 6 | 40 | English | SECS-P/10 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | SECS-P/01 |
| Marketing Analytics | 6 | 40 | English | SECS-P/08 |
| Risk Management | 6 | 40 | English | SECS-S/06 |
| Social Network Analysis | 6 | 40 | English | INF/01 |
Second trimester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Algorithms for Massive Data, Cloud and Distributed Computing | 12 | 80 | English | INF/01 |
| Optional | ||||
| Bayesian Analysis | 6 | 40 | English | SECS-S/01 |
| Digital Business Strategies | 6 | 40 | English | SECS-P/07 |
| Knowledge Extraction and Information Retrieval | 6 | 40 | English | INF/01 |
| Numerical Methods for Finance | 6 | 40 | English | SECS-S/01 |
| Patients' Needs and Healthcare Markets | 6 | 40 | English | SECS-P/01 |
| Portfolio Optimization | 6 | 40 | English | SECS-S/06 |
| Public Opinion Research | 6 | 40 | English | SPS/11 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | INF/01 SECS-S/01 |
Third trimester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Project Managements and Innovation in the Era of Big Data | 6 | 40 | English | SECS-P/08 |
Conclusive activities
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Final Exam | 9 | 0 | English | |
Optional activities and study plan rules
1 - 3 activities among the following.
Not more than two between: Fintech Industry, Portfolio Optimization, Risk Management.
Total 18 credits/ects
Not more than two between: Fintech Industry, Portfolio Optimization, Risk Management.
Total 18 credits/ects
2 - ECONOMICS (Suggested Path)
| Courses or activities | ECTS | Total hours | Language | Lesson period | SSD |
|---|---|---|---|---|---|
| Advanced Multivariate Statistics | 6 | 40 | English | First trimester | SECS-S/01 |
| Bayesian Analysis | 6 | 40 | English | Second trimester | SECS-S/01 |
| Fintech Industry | 6 | 40 | English | First 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 trimester | INF/01 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | First trimester | SECS-P/01 |
| Numerical Methods for Finance | 6 | 40 | English | Second trimester | SECS-S/01 |
| Patients' Needs and Healthcare Markets | 6 | 40 | English | Second trimester | SECS-P/01 |
| Portfolio Optimization | 6 | 40 | English | Second trimester | SECS-S/06 |
| Risk Management | 6 | 40 | English | First trimester | SECS-S/06 |
3 - BUSINESS INNOVATION (Suggested Path)
| Courses or activities | 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 | First trimester | SECS-P/11 |
| Intellectual Property for Business: Strategy and Analysis | 6 | 40 | English | First trimester | SECS-P/10 |
| Knowledge Extraction and Information Retrieval | 6 | 40 | English | Second trimester | INF/01 |
| Marketing Analytics | 6 | 40 | English | First trimester | SECS-P/08 |
| Project Managements and Innovation in the Era of Big Data | 6 | 40 | English | Third trimester | SECS-P/08 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | Second trimester | INF/01 SECS-S/01 |
4 - SOCIAL SCIENCE (Suggested Path)
| Courses or activities | ECTS | Total hours | Language | Lesson period | SSD |
|---|---|---|---|---|---|
| Advanced Multivariate Statistics | 6 | 40 | English | First trimester | SECS-S/01 |
| Digital Society | 6 | 40 | English | First trimester | SPS/07 |
| Game Theory | 6 | 40 | English | First trimester | SECS-P/01 |
| Labour Economics and Policy Evaluation | 6 | 40 | English | First trimester | SECS-P/01 |
| Patients' Needs and Healthcare Markets | 6 | 40 | English | Second trimester | SECS-P/01 |
| Public Opinion Research | 6 | 40 | English | Second trimester | SPS/11 |
| Social Network Analysis | 6 | 40 | English | First trimester | INF/01 |
| Text Mining and Sentiment Analysis | 6 | 40 | English | Second trimester | INF/01 SECS-S/01 |
First semester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| The Instruments of Gender Equality | 3 | 24 | Italian | IUS/08 |
Second semester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Equal Opportunities and Scientific Careers | 3 | 24 | Italian | SPS/09 |
| Gender Based Violence: an Interdisciplinary Approach | 3 | 20 | Italian | IUS/08 |
| Laboratory: Sustainability and Sustainable Development | 3 | 24 | Italian | AGR/01 AGR/13 IUS/01 SECS-P/01 SPS/04 |
| Teaching Workshop: the Ancient Hospital of Milan. How to Lead a Guided Tour of an Historical Monument | 3 | 20 | Italian | |
First trimester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Laboratory: "nutritional Epidemiology: Methods and Practice" | 3 | 20 | English | MED/01 |
| Laboratory: Organized Crime and Research Methodology. | 3 | 20 | Italian | SPS/09 |
Second trimester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Laboratory "cloud and Distributed Environments for Analytics in a Luxury Brand" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory "data Scientist for Business Communication" | 3 | 20 | Italian | INF/01 SECS-S/01 |
| Laboratory "official Statistics: Organization and Data of Italian National Institute of Statistics" | 3 | 20 | Italian | SECS-S/01 |
| Laboratory "reinforcement Learning" | 3 | 20 | English | INF/01 |
| Laboratory "retrieving Skills for Stem Job Description and Matching with Cvs" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory: Art, Culture and Organized Crime | 3 | 20 | Italian | SPS/07 |
| Probabilistic Modeling | 6 | 40 | English | SECS-S/01 |
Third trimester
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Laboratory "data Analytics and Digital Transformation" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory "data Solutions for Marketing" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory "data Valorization for Fintech" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory "hackathon: Deploy Machine Learning Models On Google Cloud Platform" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory "new Public Governance and Co-Production of Public Services" | 3 | 20 | Italian | SECS-P/10 |
| Laboratory "personalized Health Care" | 3 | 20 | English | MED/01 |
| Laboratory "text Data for Trading" | 3 | 20 | English | INF/01 SECS-S/01 |
| Laboratory:societies, Rights and Environmental Crime | 3 | 20 | Italian | SPS/07 |
| Laboratory:strategies for Managing Environmental Conflicts Through Participatory Mechanisms | 3 | 20 | Italian | IUS/10 |
| Workshop: Anti-Mafia Journalism | 3 | 20 | Italian | SPS/08 |
Open sessions
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Optional | ||||
| Constitution Education | 3 | 24 | Italian | IUS/08 |
Conclusive activities
There are no specific sessions for these activities (e.g. open online courses).
| Courses or activities | ECTS | Total hours | Language | SSD |
|---|---|---|---|---|
| Compulsory | ||||
| Internship/stage | 3 | 0 | English | |
Optional activities and study plan rules
5 - Students must earn 12 credits for elective activities.
Learn more
Location
Milano
Course locations
Department of Economics, Management and Quantitative Methods, Via Conservatorio 7, Milano
Department of Informatics "Giovanni degli Antoni", Via Celoria 18, Milano
Department of Informatics "Giovanni degli Antoni", Via Celoria 18, Milano
Laboratory locations
Academic guidance tutor
Reference structures
Contacts
- Degree Course E-mail
[email protected] - Facebook
http://www.facebook.com/dseunimi - Twitter
https://twitter.com/DseUnimi - Instagram
https://www.instagram.com/dse_unimi/
The tuition fees for students enrolled in Bachelor's, Master's and single-cycle degree programmes are divided into two instalments with different calculation methods and payment schedules:
- The amount of the first instalment is the same for all students
- The amount of the second instalment varies according to the ISEE University value, the degree programme and the student status (on track / off track for one year or off track for more than a year)
- An additional fee is due for online programmes
The University also offers:
- Concessions for students meeting high merit requirements
- Diversified tuition fees according to the student's home country for international students with assets/income abroad
- Concessions for international students with refugee status
Scholarships and benefits
The University provides a range of financial benefits to students meeting special requirements (merit, financial or personal conditions, international students).
Learn more
Guidance:
Admission, ranking and enrolment
Official documents