Training Programme

Fellows must complete at least 6 credits from Topical Trainings, which focus on specific scientific and methodological themes. Please note that the pair (Lecture-based+Breakout sessions) must be selected together. These activities are compulsory. While a minimum number of topical trainings is required, fellows are ecnouraged to attend as many as possible to broaden their expertise.

• Topical Training #1: Big Data

  Date: 6 February 2026, 10 AM
  Coordinated by: Prof. Stefano Lodi
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified partification and active discussion in class
  
  Description: An introduction to Big Data processing, from a methodological and computer system perspective, encompassing data collection, visualisation and efficient analysis, with a focus on predictive workflows and natural language tasks for humanities and industrial applications. The classes are organised around presentations, followed by sessions of questions and answers.

• Breakout (per TA) follow-up session on Topical Training #1: Big Data

  Date: 11 March 2026
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #2: AI For Science and Science For AI

  Date: 15 July 2026
  Coordinated by: Prof. Daniele Bonacorsi
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified partification and active discussion in class

• Breakout (per TA) follow-up session on Topical Training #2: AI For Science and Science For AI

  Date: 2 September 2026
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #3: Humanistic AI

  Date: 16 December 2026
  Coordinated by: Prof. Stefano Lodi (TBC)
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified participation and active discussion in class

• Breakout (per TA) follow-up session on Topical Training #3: Humanistic AI

  Date: December 2026
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credit: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #4: E-Infrastructures, Digital Twins, Explainability and Reproducibility in Modern Research

  Date: January 2027
  Coordinated by: Prof. Luigi Rovati & Prof. Michela Longo
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified participation and active discussion in class
  
  Description: TBD

• Breakout (per TA) follow-up session on Topical Training #4: E-Infrastructures, Digital Twins, Explainability and Reproducibility in Modern Research

  Date: February 2027
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #5: Evolution in Programming Techniques

  Date: July 2027
  Coordinated by: Prof. Renato Vacondio
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified participation and active discussion in class
  
  Description: TBD

• Breakout (per TA) follow-up session on Topical Training #5: Evolution in Programming Techniques

  Date: September 2027
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #6: Green and Sustainable Computing

  Date: November 2027
  Coordinated by: Prof. Andrea Bartolini & Prof. Paolo Ajmone
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified participation and active discussion in class
  
  Description: TBD

• Breakout (per TA) follow-up session on Topical Training #6: Green and Sustainable Computing

  Date: Decemberr 2027
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

• Topical Training #7: Responsible Data Handling, Dual-Use and Research Integrity

  Date: January 2028
  Coordinated by: Prof. Roberta Rizzo
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: Certified participation and active discussion in class
  
  Description: TBD

• Breakout (per TA) follow-up session on Topical Training #7: Responsible Data Handling, Dual-Use and Research Integrity

  Date: February 2028
  Coordinated by: Thematic Area Chairs
  Total Hours: 3
  Doctoral Credits: 0.5
  Assessment Method: reaction notes, presentation and class participation

Fellows must obtain 7 credits from Network-Wide Events, which are organized at consortium level and shared among all fellows. These events are compulsory components of the training programme.

• Thematic Workshop on Big Data

  Dates: TBD April, May, June 2026
  Location: TBD
  Coordinated by: TBD
  Total Hours: 18
  Doctoral Credits: 3
  Assessment Method: TBD

• Summer school on public engagement and dissemination

  Dates: TBD September 2026
  Location: TBD
  Coordinated by: TBD
  Total Hours: 12
  Doctoral Credits: 2
  Assessment Method: TBD

• Research symposium with industry & business incubator

  Dates: TBD April 2027
  Location: TBD
  Coordinated by: TBD
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: TBD

• Joint International Conference

  Dates: TBD 2028
  Location: TBD
  Coordinated by: TBD
  Total Hours: 6
  Doctoral Credits: 1
  Assessment Method: TBD

Fellows are required to participate in a set of project activities, mainly focused on data management and dissemination practices. These activities are compulsory but do not individually assign credits; they are considered core project obligations.

• Training on Data Management Plan (DMP)

  Date: TBD

• Training on Zenodo

  Date: TBD

• Final FutureData4EU Meeting

  Date: TBD
  Location: TBD

All FD4EU Fellows can register on the courses issued by University of Bologna and are free to attend them also in their Recruiting University, when available. DCs will be awarded according to University’s internal rules.