Modules - From data to decision 2026

The LLC "From data to decision" will consist of three modules:  

Module 1 and Module 2 (online) 

Module 1 and Module 2 will be held online through UNIBO platform with periodical meetings with an expert tutor in synchronous mode.

The two online modules will start on 28/09/2026 and are scheduled to run 1 topic per week with a break from 26/10/2026 to 08/11/2026.

Each online module awards 2 CFU, for a total of 4 CFU. 

 

In addition to 20 hours of asynchronous videolessons, participants will engage in additional activities including: 

  • online tutoring,
  • further reading and individual study,
  • active and interactive online activities, 
  • assessment activities. 

The overall workload for the online modules is 100 hours. 

 

Syllabus - Module 1 and Module 2

The syllabus of the two online modules is composed by the following topics: 

  1. Types of data, data formats, and data collection methods (UCM) 
  2. Computational thinking: algorithms, storage, modelling (UNIBO)  
  3. Basic statistical properties of data sets, data quality (Jagiellonian)  
  4. Data cleaning, transformation and linkage (UCM, Jagiellonian)  
  5. Data visualisation and interpretation (UCM)  
  6. Using simple analytics tools and building narratives (UNIBO)  
  7. Providing information to support decision-making (UoE)  
  8. Economic and societal value of data and analytics; and (KU Leuven) 
  9. Ethical and legal aspects, social impact awareness (KU Leuven).  

Module 3 (in-person)

Module 3 will be delivered in-person, at the Department of Statistical Sciences “Paolo Fortunati”- University of Bologna, approximately the last week of January 2027. It will be a full-time week dedicated to the training and application of data science skills in several fields, including: 

1. Packaging and Agrifood 

Learn how data can improve sustainability, production processes, quality control and supply chain efficiency in the agrifood and packaging sectors. Discover how analytics can support smarter resource management and product innovation. 

2. Wellness and Health Monitoring 

Understand how digital technologies and data analysis can support wellbeing, prevention and personalised services through wearable devices, behavioural data and monitoring systems. 

3. Logistics and Mobility 

Explore how data-driven approaches can optimise logistics systems, transportation networks and operational planning through predictive models and real-time information analysis. 

4. Mechanical, Automotive and Industrial Applications 

Discover how data science contributes to industrial innovation, predictive maintenance, automation and intelligent manufacturing processes in mechanical and automotive environments. 

Module 3 will involve morning seminars and afternoon workshops that will be held by experts from public institutions and private companies, faculty members belonging to the Una Europa Alliance. 

The module 3 includes 35 hours of classroom activities: 

  • 21 hours of frontal teaching, 
  • 14 hours of additional activities. 

Teaching activities will take place during a full-time week (7 hours per day for 5 days). 

The module also includes individual and/or group project work to be carried out asynchronously during the following two weeks. 

Attendance is mandatory for at least 70% of the activities.