DATA SCIENCE AND ECONOMICS (DSE) Classe LM-91-Enrolled from 2018/2019 academic year

area Scienze Politiche, Economiche e Sociali
Laurea magistrale
A.A. 2018/2019
LM-91 - Tecniche e metodi per la societa dell'informazione
Laurea magistrale
120
Crediti
Accesso
Libero con valutazione dei requisiti di accesso
2
Anni
Milano
Inglese
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 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.
http://statistiche.almalaurea.it/universita/statistiche/trasparenza?cod…
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-S01, SECS-P05, SECS-P / 01, SECS-P / 02, SECS-P07, SECS-P08

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.
No obligation

Elenco insegnamenti

Primo trimestre
Attività formative Crediti Ore totali Lingua
Obbligatorio
Graph theory, discrete mathematics and optimization 12 80 Inglese
Secondo trimestre
Attività formative Crediti Ore totali Lingua
Obbligatorio
Micro-econometrics, causal inference and time series econometrics 12 80 Inglese
Terzo trimestre
Attività formative Crediti Ore totali Lingua
Obbligatorio
Advanced microeconomics and macroeconomics 12 80 Inglese
Coding for data science and data management 12 80 Inglese
Machine learning, statistical learning, deep learning and artificial intelligence 12 80 Inglese
sarà attivato dall'A.A. 2019/2020
Non definito
Attività formative Crediti Ore totali Lingua
Obbligatorio
Algorithms for massive data, cloud and distributed computing 12 80 Inglese
Cybersecurity and privacy preservation techniques and digital security and privacy 6 40 Inglese
Facoltativo
Clustering and probabilistic modelling 6 40 Inglese
Communication research 6 40 Inglese
Datamining and computational statistics 6 40 Inglese
Digital business strategies 6 40 Inglese
Economics of government and policy evaluation 6 40 Inglese
Experimental methods and behavioural economics 6 40 Inglese
Fintech industry 6 40 Inglese
Game theory 6 40 Inglese
Global firms and markets 6 40 Inglese
Human resource management via workforce analytics 6 40 Inglese
Industrial organization and competitive policies 6 40 Inglese
Intellectual property for business: strategy and analysis 6 40 Inglese
Knowledge extraction and information retrieval 6 40 Inglese
Labour economics and policy evaluation 6 40 Inglese
Marketing analytics 6 40 Inglese
Mathematical methods for finance 6 40 Inglese
Numerical methods for finance 6 40 Inglese
Open data for new business 6 40 Inglese
Patients' needs and healthcare markets 6 40 Inglese
Polimetrics 6 40 Inglese
Portfolio optimization 6 40 Inglese
Project managements and innovation in the era of big data 6 40 Inglese
Public opinion analysis 6 40 Inglese
Quantum finance 6 40 Inglese
Risk management 6 40 Inglese
Social network analysis 6 40 Inglese
Social network analysis for business and organization 6 40 Inglese
Statistical methods for finance 6 40 Inglese
Text mining and sentiment analysis 6 40 Inglese
Attività conclusive
Attività formative Crediti Ore totali Lingua
Obbligatorio
Final exam 9 Inglese
Regole di composizione
1 - ECONOMICS (Suggested Path)
(3 activities among the following, but not more than 2 among those marked by *)
Total 18 credits/ects
Attività formative Crediti Ore totali Lingua Periodo
Clustering and probabilistic modelling 6 40 Inglese Non definito
Datamining and computational statistics 6 40 Inglese Non definito
Economics of government and policy evaluation 6 40 Inglese Non definito
Experimental methods and behavioural economics 6 40 Inglese Non definito
Game theory 6 40 Inglese Non definito
Global firms and markets 6 40 Inglese Non definito
Industrial organization and competitive policies 6 40 Inglese Non definito
Knowledge extraction and information retrieval 6 40 Inglese Non definito
Labour economics and policy evaluation 6 40 Inglese Non definito
Mathematical methods for finance 6 40 Inglese Non definito
Numerical methods for finance 6 40 Inglese Non definito
Patients' needs and healthcare markets 6 40 Inglese Non definito
Portfolio optimization 6 40 Inglese Non definito
Quantum finance 6 40 Inglese Non definito
Risk management 6 40 Inglese Non definito
Social network analysis 6 40 Inglese Non definito
Statistical methods for finance 6 40 Inglese Non definito
Text mining and sentiment analysis 6 40 Inglese Non definito
2 - BUSINESS INNOVATION (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
Attività formative Crediti Ore totali Lingua Periodo
Digital business strategies 6 40 Inglese Non definito
Fintech industry 6 40 Inglese Non definito
Human resource management via workforce analytics 6 40 Inglese Non definito
Intellectual property for business: strategy and analysis 6 40 Inglese Non definito
Marketing analytics 6 40 Inglese Non definito
Open data for new business 6 40 Inglese Non definito
Project managements and innovation in the era of big data 6 40 Inglese Non definito
Social network analysis for business and organization 6 40 Inglese Non definito
3 - SOCIAL SCIENCE (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
Attività formative Crediti Ore totali Lingua Periodo
Clustering and probabilistic modelling 6 40 Inglese Non definito
Communication research 6 40 Inglese Non definito
Datamining and computational statistics 6 40 Inglese Non definito
Game theory 6 40 Inglese Non definito
Knowledge extraction and information retrieval 6 40 Inglese Non definito
Polimetrics 6 40 Inglese Non definito
Public opinion analysis 6 40 Inglese Non definito
Social network analysis 6 40 Inglese Non definito
Text mining and sentiment analysis 6 40 Inglese Non definito
Attività conclusive
Attività formative Crediti Ore totali Lingua
Obbligatorio
Internship/stage 3 Inglese
Regole di composizione
4 - Students must earn 12 credits for elective activities.
Sede
Milano
Sedi didattiche
Department od Economics, Management and Quantitative Method, Via Conservatorio 7, Milano
Department of Informatics "Giovanni degli Antoni", Via Comelico 39, Milano
Presidente del Collegio Didattico
SILVIA SALINI
Contatti