Year: 1

Second semester

Compulsory

• Machine Learning and Statistical Learning

First trimester

Compulsory

• Coding for Data Science and Data Management
• Statistical Theory and Mathematics

Second trimester

Compulsory

• Data-Driven Economic Analysis

Third trimester

Compulsory

• Dynamic Economic Modeling

Year: 2

First trimester

Compulsory

• Cybersecurity and Protection of Personal Data: Legal and Policies Issues
• Privacy, Data Protection and Massive Data Analysis in Emerging Scenarios

Optional

• Advanced Multivariate Statistics
• Causal Inference and Policy Evaluation
• Marketing Analytics
• Network Science
• Time Series and Forecasting

Second trimester

Optional

• Bayesian Analysis
• Experimental Methods and Behavioural Economics
• Functional and Topological Data Analysis
• Project Management and Innovation
• Reinforcement Learning
• Text Mining and Sentiment Analysis

Conclusive activities

Compulsory

• Final Exam

Optional Programme Year

First trimester

Optional

• Laboratory "Data Scientist for Business Communication"
• Laboratory Conducting Experiments in Economics
• Laboratory: "Data Visualization Narratives"

Second trimester

Optional

• Laboratory "Cloud and Distributed Environments for Analytics in a Luxury Brand"
• Laboratory "Official Statistics: Organization and Data of Italian National Institute of Statistics"
• Laboratory "Retrieving Skills for STEM Job Description and Matching with CVs"
• Laboratory: "Nutritional Epidemiology: Methods and Practice"

Third trimester

Optional

• Laboratory "Data Analytics and Digital Transformation"
• Laboratory "Data Solutions for Marketing"
• Laboratory "Data Valorization for Fintech"
• Laboratory "Hackathon: Deploy Machine Learning Models On Google Cloud Platform"
• Laboratory "Personalized Health Care"
• Laboratory "Text Data for Trading"

Optional

• Additional Language Skills: Italian
• Transversal Skills

Conclusive activities

Optional

• Internship or Stage in Companies, Public or Private Bodies, Professional Orders
• Training and Orientation Internships

The course of study offers advanced skills through the study of emerging information technologies about data management and scalability of analysis systems in cloud environments, advanced statistical and mathematical techniques, as well as machine learning techniques for information extraction and classification. Furthermore, the course addresses topics about economic theory, decision theory under conditions of uncertainty, econometrics, and time-series analysis. The graduates of the DSE MSc program will receive advanced education on methodologies and tools in computer science, and quantitative and methodological notions to interpret and analyze economic phenomena using approaches that integrate business, market and social media data. Among these, the MSc program focuses on the analysis of the effects of economic policies as well as the evaluation of actions and any other activity related to the sectors of economy, marketing and business.

The DSE course bolsters the construction of solid methodological bases by addressing topics of economic theory, decision theory under uncertainty conditions, micro-econometric techniques and time-series analysis. It also fosters the study of emerging data management technologies and the scalability of analysis systems in cloud environments, as well as machine learning techniques for the extraction and classification of information.

In addition to these compulsory activities, the DSE course allows students to autonomously customize/specialize the study plan according to their own inclinations, by choosing elective courses up to 18 ECTS in total between two different educational paths, namely the "Data Science" path and the "Economic Data Analysis" path. The first kind of specialization focuses is about the aspects of methodological and technological innovation, advanced statistical methods, techniques of social media analysis and textual analysis as well as their impact on the data-driven business. A further kind of specialization 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.

These specialization activities are geared, together with the external training activities, to the preparation of the dissertation and to the final exam. Therefore, the dissertation is considered as the fulfilment of the course of study and the learning process began with the choice of the educational path.

The courses of DSE, both compulsory and elective, include lectures and laboratory classes as well as autonomous project activities and individual activities to guarantee adequate preparation also from a practical point of view, in close contact with case studies and real data.

The in-depth studies in mathematics, statistics, computer science and economics highly qualify the educational project of Data Science for Economics and they also pave the way for students interested in PhD and research programs in the areas of Data Science, Computer Science, and Economics.

The MSc program in Data Science for Economics aims to train the following professional figures:

Profile: Data Scientist

Functions: its main functions are i) to analyze and elaborate forecasts on large data flows, ii) to identify and apply the most suitable software tools and statistical techniques for their processing, iii) to create complex models for predictive data-based analysis. The Data Scientist knows the different contexts in which data emerge and she/he knows how to interact with experts from various disciplines.

Skills: statistical analysis, programming, knowledge of software tools.

Outlets: large companies, small and medium-sized enterprises, startups and Public Administration. They can work in manufacturing, telco and media, services, banking-insurance, and utilities sectors.

Profile: Data Analyst

Functions: its main functions are the identification and supervision of operational decision-making processes in direct coordination with the company executive management. They can work in marketing, business, management innovation, and finance.

Skills: baggage of theoretical knowledge about economics, statistics and computer science to support both organizational and development decisions of economic institutions and companies.

Outlets: large companies, small and medium-sized enterprises and consulting firms operating in various sectors such as manufacturing, telco and media, services, banking insurance, and utilities.

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 capable of providing new keys to interpret or evaluate economic and social phenomena.

Skills: economic theory, statistical, econometric and computer science techniques.

Outlets: large companies, Public Administration and international organizations.

Profile: Data-Driven Decision Maker

Functions: the professions included in this category perform managerial functions of high responsibility in private and public companies with an international vocation and a strong technological component, using data analysis to guide strategic and operational decisions.

Skills: a wealth of theoretical knowledge about economics, statistics and computer science to support organizational and development decisions of economic institutions and companies.

Outlets: small and medium 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: baggage of theoretical and operational notions in the field of economics, business management strategy, and the economic policies that govern them.

Outlets: they work in private or public companies in industry, commerce, business services, personal services, and companies of similar kinds as well as international and/or governmental institutions.