During its first cycle, the Department of Excellence started actively promoting the development and coordination of courses related to its core research mission. These included courses on programming, data analytics and AI (which build upon Python courses first offered by Andrea Vandin and Daniele Licari in the Spring of 2020) and courses on statistical methods (which build upon prior courses offered by Francesca Chiaromonte and Chiara Seghieri, stressing applications and the use of large contemporary datasets).

Since a.y. 2020-21, we regularly offered a sequence of coordinated courses entitled "Stats & Computing" - which utilized online or blended modalities during the pandemic, and had consistently large enrollments by undergraduate and graduate students of the Sant’Anna School, as well as by students from other programs in the Pisan academic community. Some of the materials on data analytics was also taught in different formats and venues, e.g., for the PhD Program in Computer Science at GSSI (Gran Sasso Science Institute of L'Aquila) and for the ARTES4 Industry 4.0 Competence Center.

With the beginning of the second cycle of L'EMbeDS, we are further expanding the sequence of coordinated courses -- which is now called "Computing, Data Analysis & Modeling for the Social Sciences". Materials and details for a.y. 2022-23 can be found here. At present, the sequence includes the following courses:

• SISS: Statistical Inference for the Social Sciences (taught by Chiara Seghieri) which, through one module of 20 hours, reviews basic elements of statistical inference as applied to problems in the social sciences -- integrating theory with practice in data processing and analysis through STATA, and introducing the R language.
• DMPD: Dynamic Models for Panel Data (taught by Laura Magazzini) which, through one module of 10 hours, aims at providing students advanced econometric tools for the empirical analysis of panel data models in a dynamic framework.
• PDAI: Programming, Data Analytics and AI (taught by Andrea Vandin) which, through two modules of 20 hours each, introduces the students to structured computer programming and various data processing, manipulation, visualization and analysis techniques -- using Python as reference language.
• SLLD: Statistical Learning and Large Data (taught by Francesca Chiaromonte) which, through two modules of 20 hours each, introduces the students to key topics in contemporary Statistical Learning and approaches to the analysis of high dimensional, ultra-high dimensional, and ultra-large datasets -- using R as a reference language.

We expect the number and scope of courses to grow, as L'EMbeDS contributes to the establishment of the new II level Diploma in Data Science of the Sant'Anna School.