The Master in Data Science for Complex Economic Systems is a one-year full-time postgraduate program (II level Master Degree) taught in English and welcomes students from different disciplines (e.g. economics, physics, computer science and political science).
The Master provides theoretical and methodological tools to understand and analyse complex systems which typically exhibit nonlinear behaviour resulting from the interaction of heterogeneous agents, hierarchy and continuous innovation. These properties require exploring new visions and expanding education beyond the frontier of traditional economic studies. In addition to the standard toolkit of economics and econometrics, the program takes a path-breaking perspective on advanced analytics, including big data, machine-learning network analysis, and agent-based simulation. The Master applies this pioneering approach to modelling, management, forecasting and policymaking in innovation, urban and consumption systems.
The teaching method combines a thorough theoretical training with hands-on laboratories also in collaboration with top research centres and corporations. Our faculty is recruited from top schools (e.g. Écoles Normale Supérieure de Lyon, GREQUAM), on the international academic job market. The faculty also includes scholars from the University of Turin and the Collegio Carlo Alberto.
In addition to their coursework, students interact with the faculty, fellows, and researchers of the University of Turin and of the Collegio.
Master’s graduates can apply with full recognition of course credits for admission to the Vilfredo Pareto Doctorate in Economics (curriculum in Complexity) of the University of Turin.
Candidates may apply for tuition fee waivers, research assistantships and scholarships.
- Introductory Statistics
- Mathematics For Economics
- Coding in Python
Term 1: Ideas and Instruments
- Microeconomics of Complex Economies
- Complex Networks
- Modelling Complex System
- Complexity And Agent-Based Models I
- Econometrics in R
- Data Mining
- Machine Learning
Term 2: Topics and Applications
- Innovation System: entrepreneurship and technology strategy
- Consumption System: marketing and risk strategy
- Smart Urban System and the IoT
- Innovation System Lab: patent and technology analysis
- Consumption System Lab: advanced analytics in marketing and risk
- Smart Urban System Lab: the geography of web and social media analytics