LAST UPDATE: starting from Monday 12 October

The management of student's participation will change from a half-day to a full-day. 
Group of students selected and authorized to access the building can join the lessons in presence for the whole day, not half a day anymore and combine full-day distance learning.

Events

Master Info Day @DISI, online event on 13 November 2020 at 5.00 pm.
An opportunity to learn more about the Master's Degree courses offered at the Department of Information Engineering and Computer Science.
The participants will also get informed about the EIT Digital Initiative and could interact with DISI alumni who will share their experiences.
Free participation upon registration online by 12 November at the latest.

Past events:

The first day at the University: Where is my room?

Face-to-face: you must have authorization on the UniTrentoApp. It is written on the class schedule
Video conference link: check the professor website and its announcements at Unitn.it or its personal webpage if available

As soon as you get UniTrento credentials (login and password ) login into didattica-on-line at https://webapps.unitn.it/gestionecorsi/ and select the on-line community of your courses.

You may find further information on face-to-face teaching activities on UniTrento website at https://www.unitn.it/en/ateneo/91557/attending-classes-first-semester-202021

First Semester 2020/2021, updates
update  14 September 2020

In compliance with the capacity of the classrooms and according to the current regulations, only a part of the students will be able to access the lessons in presence.

As foreseen for the Blended teaching, the face-to-face lessons will be guaranteed ONLY for first-year students of the following courses:

Undergraduate degree in Computer Science:

  • 145403 – Analisi matematica 1
  • 145405 – Geometria e algebra lineare
  • 145935 – Programmazione 1

Undergraduate degree in Computer, Communication and Electronic Engineering:

  • 145403 – Analisi matematica 1
  • 145405 – Geometria e algebra lineare
  • 145935 – Programmazione 1

Master's degree in Computer Science:

  • 145451 - Computability and computational complexity
  • 145062 - Machine learning
  • 145810 - Service Design and Engineering

Master's degree in Information and Communications Engineering: 

  • 145624 – Digital signal processing

- Area Signal Processing and Understanding (SPU)

  • 145951 - Multimedia Data Security
  • 140273 - Radar and radiolocalization 

- Area Wireless and Networking (WN)

  • 145850 - Radar and 5G Architectures and Systems
  • 145637 - Communications Systems

Master's degree in Artificial Intelligence System:

  • 145856 - Fundamentals of Artificial Intelligence
  • 145857 - Machine Learning: Module I
  • 145858 - Signal, Image and Video
  • 145860 - Law and Ethics in Artificial Intelligence

For the second- and third-year students of the Undergraduate degree courses and for the second-year students of the Master's degrees, the lessons will take place remotely only (Distance learning). 

The lessons in blended mode will be available also remotely.

The First-semester lessons will start on Monday 14 September 2020 as described in the academic calendar.

Attendance rules

Face-to-face attendance of lessons delivered in blended mode will be reserved only to students whose lessons are included in the course of study in which the student is enrolled (e.g. face-to-face attendance of Machine Learning teaching (145062) will be guaranteed to students enrolled in the master's degree course in Computer Science). 
Students who follow the lessons shared with other courses of study must attend them in remote mode.

To attend lessons in face-to-face mode, the student must have chosen this option at the moment of enrollment.

Each week the student must verify through UniTrentoApp that he/she has obtained authorization to access the building to attend the lessons, according to the timetables and groups available at this webpage .

The student is required to promptly notify to: lessons.disi [at] unitn.it his/her intention to stop attending the lessons in face-to-face mode.

Students enrolled in macro-groups who have symptoms of fever, cough, cold, loss of taste or smell or other symptoms related to Covid-19 virus are required not to go to the Mesiano or Povo campus and not to enter the building.

Students with diagnosed diseases, chronic diseases and those who make part of the population groups at risk are required to contact their doctor before enrolling in the macro-groups in face-to-face attendance.

Any regulation and/or general provision on security and fighting COVID-19 issued by the University of Trento and/or DISI is an integral part of these guidelines. 

Since each student is completely free to choose whether to attend face-to-face lessons in person or not, DISI declines any responsibility for any COVID-19 infection or in case of quarantine measures or other measures imposed by the health authorities.

General information

According to the University of Trento general indications (Covid-19 | Phase 3) and the letter from the Rector to the UniTrento students, the Department of Engineering and Computer Science will adopt the following teaching guidelines during the first semester of the academic year 2020/2021. In the implementation, the current regulations will be taken into account.

Due to the limited classroom capacity, the Blended teaching* will be activated where possible; in any other way, the Distance learning** will be applied. For more information dol.unitn.it/en

*Blended teaching: lessons in face-to-face mode for some students, while in remote mode for others.
**Distance learning: where lectures are solely provided via video conferencing and students are not expected to attend in the classroom.

Specifically, Blended teaching will be guaranteed to the first-year students of the following study courses:

  • Undergraduate Degree in Computer Science
  • Undergraduate Degree in Computer, Communication and Electronic Engineering
  • Master of Science in Computer Science
  • Master of Science in Information and Communications Engineering 
  • Master of Science in Artificial Intelligence System

The classes will be held from Monday to Friday.

The rules to access the classroom, student mobility and the list of accepted students in presence will be published on the Didattica Online website or on this webpage.

Teaching and exams 2019/2020

More information is available at this link.