A.A. 2023-2024 (cycle XXXIX)

Call for Applications – Session II

PhD in Economics, Statistics and Data Science

DEMS - University of Milano-Bicocca, Italy

The Department of Economics, Management and Statistics (DEMS) of the University of Milano-Bicocca invites applications to its PhD Programme in Economics, Statistics and Data Science (ECOSTATDATA) for the academic year 2023-24 (XXXIX cycle, Session II).

The PhD Programme is articulated in three curricula, Economics (ECO), Statistics (STAT) and Big Data & Analytics for Business (BIDAB). The length of the PhD Programme is four years, starting in late October 2023 (the precise starting date will be announced in due course on the PhD website).

The Call of Applications - Session II offers scholarships and positions on specific research projects in collaboration with national and international companies of primary importance.

The selection procedure is regulated by the official Call for Applications (Bando di Concorso) – Session II, which is expected to be published in the Doctoral School’s and in the PhD programme websites on June 30th 2023.

The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (September 2023) of the entrance examination; iii) description of the projects related to the scholarships and positions offered.

The official Call for Applications will be published here.

Introduction

ECOSTATDATA belongs to the PhD School of UniMiB, it is affiliated to DEMS, it lasts four years and it is articulated in three curricula, the original two curricula Economics (ECO) and Statistics (STAT), and, starting from cycle XXXVII (academic year 2021-2022), the “new” curriculum Big Data & Analytics for Business (BiDAB).

The first-year teaching activities are mainly devoted to structured courses (tool courses), which are compulsory. Some of these courses are fixed and specific to each curriculum, some are in common between the three curricula, some other courses are chosen by students within each curriculum.

The second-year teaching activities take the form of less structured courses (elective courses or reading groups).

In general, the first-year courses are offered by “internal” teachers, while second-year courses are often open to the collaboration of foreign instructors (visiting scholars).

The curriculum Economics (ECO)

This curriculum is indicated to students with a strong background in quantitative economics and provides advanced training in econometrics, microeconometrics, time series analysis, microeconomics and macroeconomics.

The curriculum Statistics (STAT)

This curriculum is designed for students with a strong background in statistics, both methodological and applied, and provides advanced training in probability, stochastic processes, statistical inference, Bayesian statistics, statistical learning, statistical modelling, computational statistics and data analysis.

The “new” curriculum Big Data & Analytics for Business (BiDAB)

This curriculum starts from cycle XXXVII (academic year 2021-2022), and provides students with rigorous training in data management and programming, with focus on: the analysis of large amounts of structured and unstructured data (natural language); the main paradigms of big data and data visualization, based on the use of innovative techniques of machine learning, text and web mining.

“Flexible” and “training” profiles

By means of appropriate sequences of courses, suggested and monitored by the Programme Committee and the supervisors, students are able to build up “flexible” profiles, which are mainly addressed to scientific research, both in universities or in non-academic institutions, at national or international level.

ECOSTATDATA facilitates the interaction between economic, statistical and data management skills by proposing innovative “training” profiles, which are  mainly addressed to the non-academic job market. The “training” profiles aim at:

• offering to the non-academic job market high-level skills which are not currently available;
• attracting students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented;
• eliciting the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of a PhD scholarship on specific research projects.

Length of the programme

The current length of many PhD programmes in economics, statistics and data science in Italy, including the PhD in Economics DEFAP-Bicocca and in Statistics and Mathematical Finance of UniMiB, is three years. This length is insufficient to guarantee that the PhD theses meet the quality standards achieved by the best European PhD programmes. For this reason, ECOSTATDATA lasts four years. This duration is in line with the recent choices of some of the best Italian PhD programmes in economics, statistics and data science, as well as the PhD programmes in this area offered by the most prestigious European academic institutions.

Interdisciplinarity

ECOSTATDATA fosters interdisciplinary research activities, by favouring co-tutorships between economists, statisticians and data scientists, as well as through the “flexible” and “training” profiles.

Relations with the non-academic job market

ECOSTATDATA is particularly active in collaborating with national, multi-national, high-quality and innovation-oriented companies. In particular, ECOSTATDATA is able to: i) offer high-level skills which are not currently available on the non-academic job market; ii) attract students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented; iii) elicit the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the modern instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of PhD scholarships on specific research projects.

Internationalization

The international experience which has flourished within the PhD in Economics DEFAP-Bicocca and the PhD in Statistics and Mathematical Finance of UniMiB, together with the professional networks developed by many faculty members, guarantees that ECOSTATDATA is particularly active in collaborating with prestigious foreign universities, in terms of both students and faculty members exchange programs and joint degrees.

ECOSTATDATA is managed by two bodies:

• the Programme Committee (PC), that is the executive and decision-making board composed by full professors, associate professors and researcher of UniMiB and from other renowned Italian and foreign universities and research institutions;
• the Advisory Board (AB), which collaborates with the PC to organize the teaching and research activities of the programme, is headed by the programme Coordinator and is formed by a limited number of professors and researchers who are representative of the three curricula.

The teaching activities proposed by ECOSTATDATA are organized during the first two years and differ for each curriculum, although some courses are common. Some economics courses at the first and the second year within the curriculum Economics can be offered jointly with the PhD programme in Economics and Finance of the Catholic University of Milano.

Thesis

The Programme Committee (PC) approves the (minimum) number of papers which form a typical PhD dissertation, namely 2. These papers have to be potentially publishable on high-quality internationally refereed journals.

Supervision

In order to facilitate students in identifying a sound research project and a suitable supervisor, within the first part of the year the PC organizes a presentation of the research groups which are active among the PC and the Advisory Board (AB) members. Supervisors are asked to systematically monitor the progresses made by their supervisees and periodically report to the PC about the proceedings of their dissertations.

Seminars

PhD students, especially from the second year, are strongly invited to attend the department seminars organized on a weekly basis at UniMiB. Students of both curricula are also invited to present the progress of their research work in specific seminars, which are part of the student’s evaluation process and, if possible, are jointly organized in order to enhance cross-fertilization between economists, statisticians and data scientists. 

Admission to third and fourth year

Admission to the third and fourth year is formalized by the PC, based on the evaluation of the student’s research work. Admission to the third year takes also into account the performance of each student in the second-year exams.

Admission to external evaluation

Fourth-year students should present, by the end of the year, the final version of their dissertation in front of the PC. If possible, each presentation will be assigned a discussant. The admission to the external reviewers is formalized by the PC, based on the overall evaluation of the PhD thesis.

Based on the reports of the external reviewers, students are admitted to the discussion in front of the Evaluation Committee either with minor or major revisions. Students who have successfully defended their dissertation are awarded by the Evaluation Committee the title of “PhD in Economics and Statistics” (students enrolled in cycles XXXIV, XXXV and XXXVI) or the title of “PhD in Economics, Statistics and Data Science” (students enrolled from cycle XXXVII). Students can request to (and obtain from) the Administrative Offices of UniMiB an official document reporting the specific curriculum they have been enrolled in.

ECOSTATDATA takes care of the optimal placement of its students. On this respect, the Programme Committee is very active in: i) providing students with systematic and detailed information on the job market, domestic and international, academic and non-academic; ii) advising and assisting students who intend to apply for academic positions abroad.

The research activities which characterize the PhD programme in Economics, Statistics and Data Science (ECOSTATDATA) are carried out by an active and lively community of junior and senior researchers.

Within DEMS, researchers are organized in clusters, among which the most relevant for ECOSTATDATA are:

- Business, economic and social statistics (coordinator: Prof. Pelagatti)

- Empirical microeconomics and microeconometrics (coordinator: Prof. Manera)

- Experimental and behavioural economics (coordinator: Prof. Stanca)

- Macroeconomics and macroeconometrics (coordinator: Prof. Morana)

- Microeconomics: theory and applications (coordinator: Prof. Gilli)

- Statistics (coordinator: Prof. Ongaro)

- Strategy, organization and innovation (coordinator: Prof. Torrisi)

Detailed information about people involved in each cluster can be found here.

The other two main groups of researchers supporting the programme are affiliated to the Department of Statistics and Quantitative Methods (DiSMeQ) of UniMiB and to the Department of Statistics (DiSTAT), Catholic University of Milano.

Detailed information about the research activities carried on by the DiSMeQ members can be found here.

Detailed information about the research activities carried on by the DiSTAT members can be found here.

We are very happy to announce that the new year will bring a new initiative: the ECOSTATDATA PhD Seminar Series!

This initiative aims to create a friendly environment where all PhD students at DEMS have the opportunity to present their own research or research proposal to obtain constructive feedback from peers and senior researchers.

The seminars will take place in the Seminar Room (U7-second floor 2104), every other week starting on January 19, at 17:00-18:00. After the presentations, participants will go out for an aperitivo. Here you can find the preliminary calendar (also reported below).

Regular reminders before each presentation will be sent, and we really hope you will join this initiative. Your presence and support will be key to make this a success!

The Organizers 

@Angelica Bertucci 

@Ludovica De Carolis 

@Matteo Ferraro 

@Gregorio Ghetti 

@GIORGIO MASSARI 

@Lorena Popescu 

SCHEDULE

January 19, 2023 - Giorgio Massari (Macroeconomics)

January 26, 2023 - Pietro Bomprezzi (International Finance)

February 9, 2023 - Jiefeng Bi & Luca Aiello (Bayesian Statistics & Bayesian Spatio-Temporal Statistics)

February 16, 2023 - Federico Cortese & Gregorio Ghetti (Regime switching models - Macroeconomics and Asset Pricing)

March 9, 2023 - Marco Membretti & Marco Rispoli (Macroeconomics & corporate finance) 

March 16,2023 - Alessandro Mascaro (Bayesian causal discovery)

April 6,2023 - Lorena Popescu (Health and Education Economics)

April 27, 2023 - Angelica Bertucci & Francesco Barile (Macroeconomics & Bayesian nonparametric)

May 4, 2023 - Ludovica De Carolis & Riccardo Cogo (Psychometrics & Bayesian Non Parametric)

May 18,2023 - Meneyahel Tesfaye & Francesco Ricciutelli (Financial Technology & Macroeconomics)

June 1, 2023 - Lucia Tommasiello & Marco Membretti (Bank Crisis Management & Macroeconomics)

June 15,2023 - Claudia Sartirana & Francesco Ferlaino (Innovation & Macroeconomics)

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Botond Szabo, Bocconi University , during the period October 5-27, 2021.

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Omiros Papaspiliopoulos, Bocconi University , during the period October 5-27, 2021. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca and the Fondazione Eni Enrico Mattei (FEEM), Milano, have organized the summer school on Frontiers of Energy Econometrics, at the Como Lake School of Advanced Studies, during the period September 13-17, 2021. Detailed information on the programme and the application procedure can be found on the summer school website: https://toee.lakecomoschool.org/

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Rajen Shah, University of Cambridge, during the period October 5-30, 2020. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here.

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized and hosted the course Statistical Learning and Big Data, held by Prof. Sharon Rosset, Tel Aviv University, during the period October 7-18 2019. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here.

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the 1^st CefES International Conference on European Studies, to be held at the University of Milano-Bicocca, Building U6, on June 10th-11^th 2019. Details on this event can be found here.

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the International Conference on Econometric Models of Climate Change, held at the University of Milano-Bicocca on August 29th-30^th 2019. Details on this event can be found here.

Within the Seminar Series DEMS-ECOSTAT, Prof. Peter M Robinson (LSE),  has presented the paper titled “Long-range dependent curve time series” (joint with Degui Li and Han Lin Shang). Prof. Robinson is one of the most famous econometricians worldwide and has been in the editorial boards of the most influential journals in econometrics and statistics, from Econometrica to the Journal of Econometrics, from the Journal of the American Statistical Association to the Annals of Statistics. Peter Robinson’s presentation is available here, while his paper is available here. This event has been held on February 14th 2019, 12.00am, at the Aula del Consiglio, U7, fourth floor, Piazza dell’Ateneo Nuovo 1, 20126 - Milano.

Within the celebrative events of the Twentieth Anniversary of the University of Milano-Bicocca, the Department of Economics, Management and Statistics, in collaboration with the School for Graduate Studies, has organized the International Conference on The Mathematics of Subjective Probability. This event was held on September  3rd-5th  2018, at Room U4/2, Piazza della Scienza 1, 20126 - Milano.

Within the celebrative events of its Twentieth Anniversary, the University of Milano-Bicocca, in collaboration with its School for Graduate Studies, has organized the Lectio Magistralis of Prof. Robert Engle (NYU University), winner of the 2003 Nobel Memorial Prize in Economic Sciences, on “A Financial Approach to Environmental Risk”. This event was held on June 22nd 2018, 10.00am, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

The Center for European Studies (CefES-DEMS-UNIMIB), the PhD program in Economics and Statistics (ECOSTAT-UNIMIB), and the Department of Economics, Management and Statistics (DEMS-UNIMIB) have organized the one-day international conference on Economic and Financial Implications of Climatic Change. Two plenary sessions on the economic and financial implications of climatic change have been organized on June 22^nd 2018, following Prof. Robert Engle’s talk, from 11.30am to 4.45pm, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum in Economics (ECO):

I term (October 2022 – December 2022)

- Social Network Theory (Instructor: Prof. F. Panebianco, Catholic University of Milano)

- Applications of Game Theory (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Empirical Banking (Instructor: Prof. Elena Beccalli, Catholic University of Milano)

- Advanced Asset Pricing and Portfolio Management (Instructor: Prof. A. Tarelli, Catholic University of Milano)

- Empirical Corporate Finance (Instructor: Prof. E. Croci, Catholic University of Milano)

- Programming in Python (Instructor: Prof. L. Viarengo, Catholic University of Milano)

II term (January 2023 – April 2023)

- Spatial Models (Instructor: Prof. S. Colombo, Catholic University of Milano)

- Financial Frictions (Instructor: Prof. D. Delli Gatti, Catholic University of Milano)

- The Microeconomics of International Trade (Instructor: Prof. V. Gattai, University of Milano-Bicocca)

- Innovation and Industrial Evolution (Instructor: Prof. C. Garavaglia, University of Milano-Bicocca)

- Structural VAR Models (Instructors: Proff. V. Colombo, G. Rivolta, Catholic University of Milano)

- Applied Health Economics and Policy (Instructors: Proff. G. Turati, E. Cottini, L. Salmasi, Catholic University of Milano)

Note: the RG for the curriculum ECO are offered jointly with the PhD in Economics and Finance of the Catholic University of Milano (CUM). CUM is in charge of the timetable of each RG, whose updated version can be found here. 

The following extra-RG are offered by ECOSTATDATA in the II term:

- Expected Utility and Decision Theory (Instructor: Prof. G. Cassese, University of Milano-Bicocca)

- Estimated DSGE Models (Instructor: Prof. Alice Albonico, University of Milano-Bicocca)

- Authority and Delegation (Instructor: Prof. Irene Valsecchi, University of Milano-Bicocca)

Note: the timetable of the extra-RG is available here. 

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum in Statistics (STAT):

I term (October 2022 – December 2022)

- The Dependent Dirichlet Process and Related Models (Instructors: Proff. F. Camerlenghi, B. Nipoti, University of Milano-Bicocca)

II term (January 2023 – April 2023)

- Some Issues in Statistical Modelling (Instructor: Prof. R. Borgoni, University of Milano-Bicocca)

- Empirical Bayes in Bayesian Inference (instructor: Prof. S. Rizzelli, Catholic University of Milano)

- Automated Machine Learning & Neural Architectural Search (Instructor: Prof. A. Candelieri, University of Milano-Bicocca)

- Deep Learning (Instructor: Prof. M. Borrotti, University of Milano-Bicocca)

Note: the timetable of the RG for the curriculum STAT is available here. 

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum Big Data & Analytics for Business (BIDAB):

II term (January 2023 – April 2023)

- Databases for Structured and Unstructured Data – SQL (POSTPONED) (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

- Human-centered AI (Instructor: Prof. F.M. Zanzotto, University of Roma-Tor Vergata)

Note: the timetable of the RG for the curriculum BIDAB is available here. 

I Term

The I term teaching activities start on 24 October 2022 and end on 23 December 2022. The I term exam session starts on 9 January 2023 and ends on 13 January 2023.

Note: the timetable of the I term courses is available here

The courses/modules offered during the I term for the curriculum Economics (ECO) are:

- Computational Statistics I (Instructor: Prof. G. Bertarelli, University of Pisa)

- Mathematics – Linear algebra (Instructor: Prof. N. Pecora, Catholic University of Milano)

- Mathematics I (Instructor: Prof. D. Visetti, University of Milano-Bicocca);

- Mathematics II (Instructor: Prof. F. Cavalli, University of Milano-Bicocca);

- Mathematics III (Instructor: Prof. M. Longo, Catholic University of Milano)

The courses/modules offered during term I for the curriculum Statistics (STAT) are:

- Mathematical Analysis (Instructors: Prof. C. Zanco, University of Milano; Proff. C.A. De Bernardi, E. Miglierina, Catholic University of Milano)

- Numerical Optimization (Instructor: Prof. L. Mascotto, University of Milano-Bicocca) 

The courses/modules offered during term I for the curriculum Big Data & Analytics for Business (BiDAB) are:

- Programming in Python (Instructor: Prof. M. Cesarini, University of Milano-Bicocca)

- Architecture for Big Data Processing (Instructor: Prof. V. Moscato, University of Napoli)

- Architecture for Big Data Processing Lab (Instructor: Prof. G. Sperlì, University of Napoli)

II Term

The II term teaching activities start on 16 January 2023 and end on 5 April 2023. The II term exam session starts on 17 April 2023 and ends on 21 April 2023. 

The courses/modules offered during the II term for the curriculum Economics (ECO) are:

- Econometrics I (Instructor: Prof. M. Manera, University of Milano-Bicocca)

- Econometrics I – Tutorials (Instructor: Dr. C. Cattaneo, European Institute on Economics and the Environment)

- Econometrics II (Instructor: Prof. M.L. Mancusi, Catholic University of Milano)

- Econometrics II – Tutorials (Instructor: Dr. E. Villar, Catholic University of Milano)

- Econometrics III (Instructor: Prof. A. Ugolini, University of Milano-Bicocca)

- Econometrics III - Tutorials (Instructor: Dr. D. Valenti, Fondazione Eni Enrico Mattei)

- Microeconomics I (Instructor: Prof. M. Mantovani, University of Milano-Bicocca)

- Microeconomics I – Tutorials (Instructor: Dr. F. Campo, University of Milano-Bicocca)

- Microeconomics II (Instructtor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics II – Tutorials (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics III (Instructor: Prof. L. Colombo, Catholic University of Milano)

- Microeconomics III – Tutorials (Instructor: Dr. D. Bosco, University of Milano-Bicocca)

- Microeconomics IV (Instructor: Prof. P. Bertoletti, University of Milano-Bicocca)

- Microeconomics IV – Tutorials (Instructor: Dr. G. Crea, University of Pavia)

Note: the timetable of the II term courses for the curriculum ECO is available here.

The courses/modules offered during the II term for the curriculum Statistics (STAT) are:

- Probability I & II (Instructor: Prof. F. Camerlenghi, University of Milano-Bicocca)

- Stochastic Processes (Instructor: Prof. B. Buonaguidi, Catholic University of Milano)

- R for Data Science (Instructor: Prof. A. Gilardi, University of Milano-Bicocca)

- Statistical Inference I (Instructor: Prof. A. Caponera, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum STAT is available here.

The courses/modules offered during the II term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Probability (Instructor: Prof. A. Di Brisco, University of Piemonte Orientale)

- Statistical Inference I (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum BIDAB is available here.

III Term

The III term teaching activities start on 26 April 2023 and end on 7 July 2023. The III term exam session starts on 17 July 2023 and ends on 21 July 2023. 

The courses/modules offered during the III term for the curriculum Economics (ECO) are:

Mandatory

- Macroeconomics I (Instructor: Prof. G. Femminis, Catholic University of Milano)

- Macroeconomics II (Instructor: Prof. A. Albonico, University of Milano-Bicocca)

- Macroeconomics III (Instructor: Prof. R. Masolo, Catholic University of Milano)

- Macroeconomics IV (Instructor: Dr. B. Barbaro, University of Milano-Bicocca)

- Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

- Research Methods (Instructors: Prof. T. Colussi, Catholic University of Milano; Prof. K. Aktas, University of Milano-Bicocca)

 Optional

- Finance I – Empirical Corporate Finance (Instructor: Prof. A. Signori, Catholic University of Milano)

- Finance II – Asset Pricing Theory (Instructor: Prof. A. Sbuelz, Catholic University of Milano)

- Finance III – Banking (Instructors: Proff. M. Migliavacca, F. Pampurini, Catholic University of Milano)

Note: the timetable of the III term courses for the curriculum ECO is available here.

The courses/modules offered during the III term for the curriculum Statistics (STAT) are:

Mandatory

- Statistical Inference II (Instructor: Prof. A. Solari, University of Milano-Bicocca)

- Bayesian Statistics (Instructors: Prof. R. Argiento, University of Bergamo; Proff. B. Nipoti, T. Rigon, University of Milano-Bicocca)

- Data Management (CANCELLED)

Optional

- Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

Note: the timetable of the III term courses for the curriculum STAT is available here.

The courses/modules offered during the III term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Technology and Innovation Management (Instructors: Proff. S. Torrisi, L. D'Agostino, F. Di Pietro, M. Guerzoni, University of Milano-Bicocca)

- Machine Learning (Instructor: Prof. L. Malandri, University of Milano-Bicocca)

- Natural Language Understanding (CANCELLED)

- Social Media Analytics (Instructor: Prof. R. Boselli, University of Milano-Bicocca)

Note: the timetable of the III term courses for the curriculum BIDAB is available here.

IV Term

The IV term teaching activities start on 4 September 2023 and end on 20 October 2023. The IV term exam session starts on 23 October 2023 and ends on 27 October 2023. 

Note: the timetable of the IV term courses is under construction and is currently shared with all the ECOSTATDATA students, who can monitor online any updates/modifications.

The courses/modules offered during the IV term for the curriculum Statistics (STAT) are:

- Statistical Learning (POSTPONED)

- Statistical Modelling I (Instructor: Prof. F. Castelletti, Catholic University of Milano)

- Statistical Modelling II (Instructor: Prof. F. Greselin, University of Milano-Bicocca)

- Statistical Modelling III (Instructor: Dr. S. Verzillo, European Commission - Joint Research Center)

- Statistical Modelling IV (Instructors: Prof. F. Pennoni, University of Milano-Bicocca; Prof. F. Bartolucci, University of Perugia)

The courses/modules offered during the IV term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Statistical Modelling I (Instructor: Prof. F. Castelletti, Catholic University of Milano)

- Statistical Inference II (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

- Explainable AI for Business Value (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

- Deep Learning and Computer Vision for Business (Instructor: Prof. E. Frontoni, Polytechnic University of Marche, TBC)