The Program is worth a total of 60 credits (ECTS), for a total amount of 1.500 hours, divided as follows:
- 440 hours of on-campus lectures and distance learning
- 1060 hours of Labs, Individual Study and Final Research Project.
Course contents and methodology
During the course students will learn to:
- Analyze economic data using traditional econometric models and ML/AI tools
- Evaluate public policies and corporate strategies
- Develop simulation models for ex-ante evaluations of the effect of interventions on economic systems
- Provide expert advice to policy makers relying on a solid understanding of both institutional and political contexts
- Provide private businesses' management with quantitative evidence to support strategic decisions
Combining the theoretical presentation with laboratory activities students will also acquire the necessary programming skills with the main open source statistical and data management softwares.
Students will be able to apply for a visiting period at one of the Institutions within the collaborative network of the Master. Allocation of students to the available visiting positions is responsibility of the scientific committee, according to host institutions' posted places, topics and students’ abilities.
The blended teaching format includes a fully structured, on-line assisted preliminary learning phase, an on-campus phase with both lectures and laboratory activities, a supervised project work activity. Students will be able to apply for a visiting periods at one of the Institutions within the collaborative network of the Master to deliver their project work. Allocation of students to the available positions is responsibility of the scientific committee, according to host institutions' posted places, topics and students’ abilities.
The course is divided into 9 didactic modules distributed over three subject areas.
1. Data, databases and coding
- Data and Databases - Big data and statistical data; data procurement and querying.
- Coding for data analytics - Python and R.
2. Economic Foundations
- Economics and Institutions - Foundations of micro- and macroeconomics
- Big Data Applications for Policy Analysis - Selected applications from the literature
- Simulation models - Micro- and macro-simulations; Agent Based Modelling
- Specialized tracks - Optional courses specialized in business- and public policies applications
3. Statistics and Econometrics
- Foundation of statistics - Probability and inference; Exploratory data analysis and presentation
- Data Modelling - Basic econometrics; Data Mining and Machine Learning; Fundamentals of AI and Natural Language Processing
- Causal models for decision making - Advanced econometrics for causal inference; Social experiments
Download the study plan in pdf format.