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Laboratories

Laboratories are elective activities promoted by partner companies or institutions (e.g., universities, research institutes) and approved by the Faculty Board of DSE.

Labs usually consist of 20 hours of practical activities and are organized throughout the Academic Year (see below the calendar, usually updated in October for the upcoming year).

Typically, for a Lab, only a small number of students can be admitted due to logistics constraints. For each Lab, a call for application is published on this webpage a few weeks before the Lab starts. Candidates will be selected by the involved companies/institutions according to CV and motivations. The Faculty Board is not involved in the selection process of candidates.

The credits earned from labs will be considered as elective credits (a total of 9 elective credits are expected in the plan of study of a DSE student). Some laboratories, when explicitly declared, are valid as 3 ECTS of soft skills. Laboratories ARE NOT VALID as stage/internship. A minimum attendance of 75% is required for the assignment of credits.

Contacts

Prof. Silvia SALINI

 

Laboratories a.y. 2024-2025

Data Visualization Narratives - Prof.ssa Beatrice Gobbo
[either elective or transversal/soft skill credits]

Official Statistics: Organization and Data of Italian National Institute of Statistics - Istituto Nazionale di Statistica (ISTAT)
[either elective or transversal/soft skill credits]

Business & Marketing Data Driven Analysis - prof. Edoardo Piccolotto
[either elective or transversal/soft skill credits]

Data Storytelling: Effective Visualisation of Data with Different Tools - Softlab SpA
[either elective or transversal/soft skill credits]

Hackathon: Deploy Machine Learning Models on Google Cloud Platform - Prof. Emanuele Guidotti
[either elective or transversal/soft skill credits]

Nutritional Epidemiology: Methods and Practice - Prof.ssa Edefonti and Prof.ssa Bravi
[either elective or transversal/soft skill credits]

Personalized Health Care - Prof. Biganzoli
[either elective or transversal/soft skill credits]

The Economics of Big Science - Prof. Johannes Gutleber (CERN)
[elective credits]

Big Questions for Labor Economists - prof. Daniel Kreisman
[elective credits]

Drive Digital Transformation with Data Analytics - Deloitte
[either elective or transversal/soft skill credits]

 


 

Laboratories a.y. 2023-2024
  • Data Visualization Narratives - Prof. Beatrice Gobbo 
    [both elective credits or transversal skill activity]
     
  • Conducting Experiments in Economics - Prof. Antonio Filippin
     
  • Data Scientist for Business Communication (Assolombarda)  - (also ascribable/available as Transversal Skill); Prof. Silvia Salini
  • Official Statistics: organisational and data of the ISTAT (ISTAT) - (also ascribable/available as Transversal Skill); Prof. Silvia Salini
  • Modelling, Clustering, Forecasting and Presenting Post Trade Data (Euronext) - INTERNSHIP ONLY

 

  • Football Analytics (Soccerment) - (also ascribable/available as Transversal Skill);

 

  • Cloud and Distributed environments for analytics in a Luxury Brand (Prada) - (also ascribable/available as Transversal Skill);

  • Advanced Analytics in Marketing (Intarget)

 

  • Data Analytics stories with Power BI Lab

 

  • Data Story telling / Data Visualization (Softlab)

 

  • Hackathon: Deploy Machine Learning Models on Google Cloud Platform (Guidotti)

 

  • ML in finance: forecasting and usage of large language models (Ammagamma Srl) - (also ascribable/available as Transversal Skill);

 

  • Nutritional Epidemiology - Prof.ssa Edefonti and Prof.ssa Bravi

 

  • Personalized Healthcare - Prof. Biganzoli

Lectures on Optimal Transport and Economic Applications

Description: See the attached syllabus

Instructor: Alfred Galichon, Visiting Professor from New York University in Paris

Academic Year: 2023-2024, 20 hours/3 credits

Period: first and third term

Available seats: limitless (open to DSE + Ph.D. in Economics students)

Timetable: (all classes in the Computer Room on the 2nd floor, via Livorno 1)

  • Thu 26 Oct 2023 - from 14:30 till 18:30
  • Fri 27 Oct 2023 - from 10:30 till 12:30 + from 14:30 till 18:30
  • Thu 6 Jun 2024 - from 14:30 till 18:30
  • Fri 7 Jun 2024 - from 10:30 till 12:30 + from 14:30 till 18:30

Registration: via form shared by email (you will be notified when you can apply)

Machine Learning for Causal Inference in Econometrics

Description: See the attached syllabus

Instructor: Anna Simoni, Visiting Professor from CNRS and CREST (National Center of Scientific Research - Campus École Polytechnique Palaiseau [France])

Academic Year: 2023-2024, 16 hours/3 credits

Period: second and third term

Available seats: 20 (open to DSE + Ph.D. in Economics students)

Timetable: (updated on Mar 3 2024)

  • Thu 15 Feb 2024 │14:30 – 16:30 DEMM Seminar Room (2nd floor) - via Conservatorio 7
  • Mon 19 Feb 2024 │10:30 – 12:30 DEMM Seminar Room (2nd floor) - via Conservatorio 7
  • Tue 20 Feb 2024 │10:30 – 12:30 DEMM Seminar Room (2nd floor) - via Conservatorio 7
  • Wed 21 Feb 2024 │12:30 – 14:30 DEMM Seminar Room (2nd floor) - via Conservatorio 7
     
  • Wed 10 Apr 2024 | 11:00 – 12:30 DEMM Seminar Room (2nd floor) - via Conservatorio 7
  • Fri 12 Apr 2024 | 14:30 – 16:00 DEMM Seminar Room (2nd floor) - via Conservatorio 7
  • Mon 15 Apr 2024 | 10:30 – 13:30 Seminar Room via Livorno 1

Registration: via form shared by email (you will be notified when you can apply)

Introduction to general and generalized linear models: Classical and Bayesian Inference

Description: See the attached syllabus

Instructor: Luciana Dalla Valle, Visiting Professor from University of Plymouth (UK)

Academic Year: 2023-2024, 20 hours/3 credits

Period: third term

Available seats: max. 20 (open to DSE students only)

Timetable: from Monday 17 June until Friday 21 June 2024, everyday from 14:00h till 18:00h in DEMM Seminars Room "Giorgio Pizzutto" (2nd floor)

Registration: via form shared by email (you will be notified when you can apply)

Important: Students will be asked to bring their own laptop with RStudio and JAGS softwares installed. Please follow the instructions available here.

Laboratories a.y. 2022-2023
  • Nutritional Epidemiology: methods and practice (1st trimester) - Proff. Valeria Edefonti, Francesca Bravi
  • Official Statistics: organization and data of Italian National Institute of Statistics - ISTAT (2nd trimester) - Prof.ssa Silvia Salini

 

  • Cloud and Distributed Environments for Analytics in a Luxury Brand - Prada Group (2nd trimester) - Prof. Stefano Montanelli

 

  • Data Scientist for Business Communication - Assolombarda (2nd trimester) - Prof.ssa Silvia Salini

 

  • Reinforcement Learning - within the university (2nd trimester) - Prof. Cesa Bianchi

 

  • Retrieving Skills from STEM Job Descriptions and Matching with CVs - Open Search Group (2nd trimester) - Prof.ssa Silvia Salini

 

  • Modelling, Clustering and Forecasting Post Trade data (Borsa Italiana) - INTERNSHIP (2nd trimester) - N.D.
  • Data Valorization for Fintech - AcomeA SGR S.p.A. - Gimme5 (3rd trimester) - Prof.ssa Silvia Salini

 

  • Data Solutions for marketing - Intarget Group (3rd trimester) - Prof. Stefano Montanelli

 

  • Hackathon: Deploy Machine Learning Models on Google Cloud Platform - Emanuele Guidotti (3rd trimester) - Prof. Stefano Montanelli

 

  • Text data for trading - Ammagamma (3rd trimester) - Prof.ssa Silvia Salini

 

  • Personalized Health Care - within the university (3rd trimester) - Proff. Federico Ambrogi, Elia Biganzoli

 

  • Data Analytics & Digital Transformation - Deloitte (3rd trimester) - Prof.ssa Silvia Salini