Master's Degree in Data Science for Economics (DSE)
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
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STUDY FORMAT
On-Campus
Introduction
This master's degree course, entirely delivered in English, aims to provide advanced education on methodological methods and tools in computer science (including cloud environments and machine learning), statistics, and mathematics designed to interpret and analyze complex phenomena in the fields of economics. In addition to some compulsory activities, students can autonomously customise the study plan by choosing elective courses between two different educational paths: the "Data Science" and Economic Data Analysis" path.
The Master of Science in “Data Science for Economics” (DSE) aims to provide a modern, effective educational programme for students interested in data science issues, with a special focus on applications to the economic field.
The DSE program started in 2018 and it was re-designed in 2022 to join the emerging “LM-DATA” CUN class.
DSE strongly leverages STEM disciplines to provide solid, coherent training on quantitative and methodological methods and tools of Information Technology (IT) as well as Statistics and Mathematics to interpret and analyze complex phenomena in the field of economy. DSE is conceived as a flexible educational programme with an important number of elective courses. Supported by the tutors, a student customizes the study plan through the choice between two alternative paths, namely “Data Science” and “Economic Data Analysis” paths, to further enhance STEM-oriented and economic-oriented competencies, respectively. The external stakeholders of DSE are constituted by selected territorial companies and organizations focused on data science missions, and they are widely involved in the programme development in the form of lab and internship opportunities.
Given the multidisciplinary nature of the acquired knowledge and skills, the graduates of DSE can work in a variety of professional areas: small, medium, and large IT companies and research centres, companies and public bodies focused on big data management, R&D labs, innovative start-ups, healthcare companies, biomedical and pharmaceutical industries, economic and financial consulting firms, Public Administrations, National Statistical Institutes, National Banks.
Given their solid methodological education, the graduates of DSE can continue their academic experience in a PhD programme; possible scientific fields are Computer Science, Mathematics, Statistics, and Economics.
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Admissions
Curriculum
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
Program Outcome
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.
Program Tuition Fee
Career Opportunities
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.