Dottorato di Ricerca in 
Information Technology and Electrical Engineering (ITEE)

20-22-25-26/03   4-5/04/2024    Ad hoc course

Title: I pilastri della trasformazione digitale

Lecturer:  dr. Francesco Tortorelli - Independent consultant, former AgID director -

Period: 20-22-25-26/03   4-5/04/2024

Assessment test:  TBD 

Credits:  3

Participants are requested to send an e-mail to Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo. by February 29, 2024, with the following information:

Student name and surname, name of the PhD course, PhD cycle

Il corso è in lingua italiana / The course will be held in Italian

Le Lezioni si terranno in Aula Seminari, I piano, DIETI, Palazzina 3, Via Claudio, 21 – 80125 – Napoli.

For information: Prof. Nicola Mazzocca (DIETI, UniNA) – Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo.

 I Pilastri Trasformazione Digitale

23-25-30/01/2024  01-06-08/02/2024     Ad hoc course

Title: Using Deep Learning properly

Lecturer:  dr. Andrea Apicella - Dieti - Unina - 

Period:  23-25-30/01/2024  01-06-08/02/2024

Assessment test:   TBD

Lesson: 6

Credits:  4

The lectures are held in C2A room, ground floor of building #3, via Claudio 21, Napoli

Participants are requested to join the following MS Teams group: https://teams.microsoft.com/l/team/19%3aO83S27sneGGzE6FysYhB3P7OpTu-49maT0JT0RNwL_U1%40thread.tacv2/conversations?groupId=dc321d84-072e-4965-95e3-0f0ddc872860&tenantId=2fcfe26a-bb62-46b0-b1e3-28f9da0c45fd

Once accepted in the Teams group, students have to fill the following .xlsx file with their information:

https://communitystudentiunina-my.sharepoint.com/:x:/g/personal/andrea_apicella_unina_it/ERyITFguH7JKr99o2XVA7z4B216wzWt0fnKFS_BJ8jOGlg?e=dendtT

For information: Andrea Apicella, Ph.D. (DIETI, UniNA) – Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo.

 Using Deep Learning properly

08-09-15-16-22-23/02/2024     Ad hoc course

Title: IoT Data Analysis

Lecturer:  prof. Raffaele Della Corte - Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione (DIETI-UNINA)

Period: 08-09-15-16-22-23/02/2024

Assessment test:  01/03/2024 

Credits:  4

By 19th January 2024, participants are requested to join the following MS Teams group:

https://teams.microsoft.com/l/team/19%3aJbvyf0UMvKsxVruFylVI4Nae5bhqqwIhZMe2FGsOM

9I1%40thread.tacv2/conversations?groupId=fe0d2607-212d-4abf-8a92-

ba972b421d4a&tenantId=2fcfe26a-bb62-46b0-b1e3-28f9da0c45fd

Once accepted in the Teams group, students have to fill the following .xlsx file with their

information (i.e., Student name and surname, e-mail, name of the PhD course, PhD cycle):

https://communitystudentiunina.sharepoint.com/:x:/s/IoTDataAnalysis-ITEEA.A.2023-

24/EXLbGuHnfxtGtJzMKNujA-ABiiFTyJ81oqaYTfNsTar-SQ?e=dMQLix

The course is conducted on-site. However, students pursuing their PhD period abroad (for

research purposes) have the option to request remote attendance for classes via MS Teams.

For information: Prof. Raffaele Della Corte (DIETI, UniNA) – Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo.

 IoT-DataAnalysis

15-19-21-23-27-29/02/2024

                                                                              Ad hoc course

Title:  Statistical data analysis for science and engineering research

Lecturer:  prof. Roberto Pietrantuono - DIETI, Unina

Period:  15-19-21-23-27-29/02/2024

Assessment test:  TBD

Credits:  4 

Lectures are also streamed on the University platform Microsoft Teams. Team Code: 82w8tmr

The lectures are held in Aula Seminari 1° floor of building #3, via Claudio 21, Napoli - DIETI

Doctoral Students interested in the module are requested to join the team (code 82w8tmr) and fill in

the “Participants Info” file available under the “File” tab.

For information: Prof. Roberto Pietrantuono (DIETI, UniNA) – Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo.

 Statistical Data Analysis