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

area Scienze Politiche, Economiche e Sociali
Master programme
A.Y. 2018/2019
LM-91 - Tecniche e metodi per la societa dell'informazione (EN)
Master programme
120
ECTS
Access
Open with entry requirements examination
2
Years
Milano
English
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…

Courses list

First trimester
Courses or activities ECTS Total hours Language
Compulsory
Graph Theory, Discrete Mathematics and Optimization 12 80 English
Second trimester
Courses or activities ECTS Total hours Language
Compulsory
Micro-econometrics, Causal Inference and Time Series Econometrics 12 80 English
Third trimester
Courses or activities ECTS Total hours Language
Compulsory
Advanced Microeconomics and Macroeconomics 12 80 English
Coding for Data Science and Data Management 12 80 English
Machine Learning, Statistical Learning, Deep Learning and Artificial Intelligence 12 80 English
be activated by the A.Y. 2019/2020
Undefined
Courses or activities ECTS Total hours Language
Compulsory
Algorithms for Massive Data, Cloud and Distributed Computing 12 80 English
Cybersecurity and Privacy Preservation Techniques and Digital Security and Privacy 6 40 English
Optional
Clustering and Probabilistic Modelling 6 40 English
Communication Research 6 40 English
Datamining and Computational Statistics 6 40 English
Digital Business Strategies 6 40 English
Economics of Government and Policy Evaluation 6 40 English
Experimental Methods and Behavioural Economics 6 40 English
Fintech Industry 6 40 English
Game Theory 6 40 English
Global Firms and Market 6 40 English
Human Resource Management Via Workforce Analytics 6 40 English
Industrial Organization and Competitive Policies 6 40 English
Intellectual Property for Business: Strategy and Analysis 6 40 English
Knowledge Extraction and Information Retrieval 6 40 English
Labour Economics and Policy Evaluation 6 40 English
Marketing Analytics 6 40 English
Mathematical Methods for Finance 6 40 English
Numerical Methods for Finance 6 40 English
Open Data for New Business 6 40 English
Patients' Needs and Healthcare Markets 6 40 English
Polimetrics 6 40 English
Portfolio Optimization 6 40 English
Project Managements and Innovation in the Era of Big Data 6 40 English
Public Opinion Analysis 6 40 English
Quantum Finance 6 40 English
Risk Management 6 40 English
Social Network Analysis 6 40 English
Social Network Analysis for Business and Organization 6 40 English
Statistical Methods for Finance 6 40 English
Text Mining and Sentiment Analysis 6 40 English
Conclusive activities
Courses or activities ECTS Total hours Language
Compulsory
Final Exam 9 English
Study plan rules
1 - ECONOMICS (Suggested Path)
(3 activities among the following, but not more than 2 among those marked by *)
Total 18 credits/ects
Courses or activities ECTS Total hours Language Lesson period
Clustering and Probabilistic Modelling 6 40 English Undefined
Datamining and Computational Statistics 6 40 English Undefined
Economics of Government and Policy Evaluation 6 40 English Undefined
Experimental Methods and Behavioural Economics 6 40 English Undefined
Game Theory 6 40 English Undefined
Global Firms and Market 6 40 English Undefined
Industrial Organization and Competitive Policies 6 40 English Undefined
Knowledge Extraction and Information Retrieval 6 40 English Undefined
Labour Economics and Policy Evaluation 6 40 English Undefined
Mathematical Methods for Finance 6 40 English Undefined
Numerical Methods for Finance 6 40 English Undefined
Patients' Needs and Healthcare Markets 6 40 English Undefined
Portfolio Optimization 6 40 English Undefined
Quantum Finance 6 40 English Undefined
Risk Management 6 40 English Undefined
Social Network Analysis 6 40 English Undefined
Statistical Methods for Finance 6 40 English Undefined
Text Mining and Sentiment Analysis 6 40 English Undefined
2 - BUSINESS INNOVATION (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
Courses or activities ECTS Total hours Language Lesson period
Digital Business Strategies 6 40 English Undefined
Fintech Industry 6 40 English Undefined
Human Resource Management Via Workforce Analytics 6 40 English Undefined
Intellectual Property for Business: Strategy and Analysis 6 40 English Undefined
Marketing Analytics 6 40 English Undefined
Open Data for New Business 6 40 English Undefined
Project Managements and Innovation in the Era of Big Data 6 40 English Undefined
Social Network Analysis for Business and Organization 6 40 English Undefined
3 - SOCIAL SCIENCE (Suggested Path)
(3 activities among the following)
Total 18 credits/ects
Courses or activities ECTS Total hours Language Lesson period
Clustering and Probabilistic Modelling 6 40 English Undefined
Communication Research 6 40 English Undefined
Datamining and Computational Statistics 6 40 English Undefined
Game Theory 6 40 English Undefined
Knowledge Extraction and Information Retrieval 6 40 English Undefined
Polimetrics 6 40 English Undefined
Public Opinion Analysis 6 40 English Undefined
Social Network Analysis 6 40 English Undefined
Text Mining and Sentiment Analysis 6 40 English Undefined
Conclusive activities
Courses or activities ECTS Total hours Language
Compulsory
Internship/Stage 3 English
Study plan rules
4 - Students must earn 12 credits for elective activities.
Course location
Milano
Learning centers
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
Contacts