The programme

Here you can find an overview of the degree programme, including information on its organisation and regulations, as well as a number of useful information. In addition, this section includes an overview of the University’s Quality Assurance system and the Student Orientation services available to prospective students, to help them choose the right course for them.

Student orientation services

The new website of the Student Orientation Office, with new form and content, is the result of a long process aimed at providing a better and more comprehensive service to its many users. Users are mostly secondary school pupils approaching the University for the first time, and schools' University Orientation Services which organise activities to assist their pupils in post-school choices. Making a decision means choosing the best alternative to satisfy one's expectations, preferences and aspirations. 
 
More details: www.univr.it/orientamento (italian page)

sportello telefonico: dal lunedì al venerdì, dalle ore 9:00 alle 13:00.

Find out more

Course of study in brief

The objective of the master's degree course in "Artificial Intelligence" (AI) is to train experts in artificial intelligence, capable of developing intelligent agents in a wide range of application contexts.
The course is aimed at students, graduates of science (e.g., Computer Science, Physics, Mathematics) or engineering (e.g., Computer Science, Bioengineering, Electronics, Management) degree programs, who have a solid foundation in computer science.
The need to train specialists in the fields of computer science and ICT is clear from the AlmaLaurea 2021 Report in which it is shown that computer science and ICT are the educational fields with the highest demand and the highest net income 5 years after graduation, followed immediately by degrees in Industrial and Information Engineering.

The Master's Degree in Artificial Intelligence aims to train specialists in the field of computer science (Master's Degree Class LM18) capable of developing tools, mostly software, based on the techniques and methodologies specific to Artificial Intelligence (AI). It is also widely recognized how these technologies are being characterized in the landscape of computer science and information technology as a unified corpus for methodologies employed (automatic reasoning and machine learning) and represent one of the most developing areas in the field of STEM sciences.
The main educational objective is to acquire methods and tools to develop fundamental techniques of artificial intelligence, and to design agents capable of autonomously acquiring knowledge and developing models and strategies. Possible applications include areas such as: ecology (e.g., environmental monitoring, climate change), economics (e.g., finance and insurance markets), sustainable growth (e.g., smart building, smart cities, smart grids), medicine (e.g., diagnostics, tele-medicine), product and service industries (e.g., AI-assisted programming, automatic text and speech translation, social signal processing, cybersecurity, autonomous robots, assisted and autonomous driving systems), gaming and entertainment, intelligent, social and human-centered user interfaces (Human Centered Design).
With this in mind, the course places special emphasis on issues related to the development of methods and technologies, mainly software, of artificial intelligence that are secure, reliable, fair, interpretable, i.e., capable of explaining one's decisions, according to the new paradigm of XAI ("eXplainable Artificial Intelligence"). In relation to these educational objectives, the Master's Degree Course in Artificial Intelligence proposes teachings aimed at obtaining specific skills mainly in the fields of computer science and information engineering, with an emphasis on methods and tools to develop artificial intelligence techniques, with particular reference to machine learning, intelligent agents, automatic reasoning, computer vision, knowledge representation, planning, game theory, natural language processing, logic, and the history of artificial intelligence. These teachings will be complemented by learning paths that will enable students to develop knowledge on: analytical/quantitative tools, such as methods and models of probability calculus and physics, inferential statistics, optimization techniques, and decision theory; epistemological and philosophical aspects underlying computational thinking; ethical foundations for the management of artificial intelligence technologies; legal aspects and principles concerning the regulation for the management of artificial intelligence-based technologies; and tools for the development of applications in economics and finance.

 

More information about, e.g., contact people and international opportunities, can also be found at the dedicated website.

Course presentation event - May 17, 2022

Here are the presentation slides of the event; below is the YouTube playlist of the speeches.

  • Degree type Corsi di laurea Magistrale
  • Duration 2  years
  • Part-time Study option available Yes
  • Admissions Subject to entry requirements
  • Degree class LM-18
  • S.T.E.M. course Yes
  • Location verona
  • Language English
Obiettivo del corso di Laurea Magistrale in Artificial Intelligence è far acquisire alle studentesse ed agli studenti le conoscenze e competenze multidisciplinari necessarie per la fattiva declinazione di competenze informatiche nell’ambito dell’intelligenza artificiale e delle discipline che la caratterizzano. Le studentesse e gli studenti dovranno conseguire solide capacità negli ambiti dell’informatica e dell’ingegneria, con particolare enfasi su metodi basati su rappresentazioni “simboliche” di problemi, cioè rappresentazioni che utilizzano e manipolano simboli, come le rappresentazioni basate sulla logica, e metodi di ricerca nello spazio degli stati; metodi basati su rappresentazioni probabilistiche, tipiche dell’apprendimento automatico guidato dai dati; metodi di intelligenza artificiali le cui decisioni possano essere comprese dall’essere umano, in linea con il forte trend attuale di regolamentazione dell’intelligenza artificiale per applicazioni che coinvolgano agenti autonomi ed esseri umani.
Tali conoscenze saranno coadiuvate da approfondimenti in altre discipline volte a sviluppare percorsi di apprendimento riguardanti: lo sviluppo di modelli matematici e la risoluzione di problemi di ottimizzazione; l’utilizzo di principi e fonti del diritto riguardanti la gestione di strumenti di intelligenza artificiale; lo svluppo di applicazioni in ambito economico e finanziario; la conoscenza delle basi etiche per la gestione di tecnologie di intelligenza artificiale in contesto produttivo ed in relazione all’interpretazione dei fenomeni socio-economici ad esso connessi.
Sono stati individuati, in particolare, i seguenti obiettivi formativi specifici:
• una consistente base teorica e pratica su machine learning e deep learning che fornisca allo studente le basi e lo stato dell’arte nel settore;
• una consistente base teorica e pratica su planning e scheduling, ovvero programmazione simbolica ed a vincoli che costituiscono le fondamenta dell'AI classica;
• una consistente base teorica e pratica su elementi di reinforcement learning per la progettazione di sistemi di intelligenza artificiale adattivi;
• una consistente base teorica e pratica su elementi di programmazione avanzata per AI al fine di fornire allo studente le basi per la progettazione, l’assemblaggio ed il deployment (e.g., su cloud) di architetture software finalizzate all’AI;
• una consistente base teorica e pratica su metodi per lo studio, la analisi e la valutazione della cooperazione tra agenti, in questo caso algoritmi di AI ed operatori umani;
• aspetti metodologico-operativi della matematica, della statistica, della fisica, del diritto e dell’etica, relativi ai problemi di intelligenza artificiale;
• La comprensione dell’impatto delle soluzioni di intelligenza artificiale nel contesto sociale;
• La conoscenza delle proprie responsabilità professionali ed etiche;
• La conoscenza degli strumenti cognitivi di base per l’aggiornamento continuo delle proprie conoscenze.
Tutte queste conoscenze avranno l’obiettivo di consentire alle studentesse ed agli studenti di saper sviluppare metodi, strumenti e tecnologie complessi basati sull’intelligenza artificiale in vari ambiti applicativi.
Questi obiettivi forniscono le basi culturali, scientifiche e tecniche del laureato in Artificial Intelligence e considerano le richieste emerse dall’incontro con gli stakeholder.

I corsi sono organizzati nei due anni in modo da garantire una corretta sequenzialità nell’acquisizione dei concetti. In particolare, le conoscenze relative ai fondamenti teorici dell’Intelligenza Artificiale sono fornite nei corsi del primo anno. Le consocenze più specifiche, riguardanti tecniche avanzate, specifiche applicazioni dell’Intelligenza Artificiale ed attività affini sono fornite nel secondo semestre del primo anno e nel secondo anno. L’armonizzazione dei contenuti degli insegnamenti è coadiuvata dalla presenza di laboratori che integrano diverse conoscenze e capacità applicative, e sono atti a sviluppare capacità applicative, relazionali e di team-working. I laboratori servono altresì come preparazione al tirocinio. L’armonizzazione dei contenuti è supportata dalla presenza di esami applicativi e per natura interdisciplinari. Nel secondo anno lo studente dovrà inoltre svolgere un tirocinio formativo e di orientamento.

PROFILI PROFESSIONALI

ARTIFICIAL INTELLIGENCE SPECIALIST

Funzione in un contesto di lavoro
Ricopre ruoli quale il coordinatore di progetti di intelligenza artificiale, l’analista di software con funzionalità di intelligenza artificiale, lo sviluppatore di moduli software con funzionalità di intelligenza artificiale, l’integratore di tali moduli o l’addetto alla verifica di tali moduli. In generale, l’AI Specialist assume ruoli di responsabilità nella progettazione e sviluppo di metodi e strumenti di intelligenza artificiale per realizzare sistemi capaci autonomamente di acquisire conoscenza ed elaborare modelli e strategie. Esempi di tali sistemi sono: sistemi di gestione della conoscenza e di estrazione di conoscenza da grandi quantità di dati (e.g., reti sociali, internet); sistemi di intelligenza artificiale per l'industria del cinema e dei videogiochi; sistemi di IA per estrarre, gestire e processare dati relativi al monitoraggio ambientale e cambiamenti climatici; sistemi di IA per economia e finanza; sistemi di IA per la crescita sostenibile (e.g., “smart building”, “smart cities”, “smart grids”); sistemi di IA per la medicina (e.g., diagnostica, tele-medicina); sistemi di IA per l’industria dei prodotti e dei servizi (e.g., “AI-assisted programming”, traduzione automatica del testo e del parlato, cybersecurity, robot autonomi, sistemi di guida assistita ed autonoma).

Competenze associate alla funzione

  • Capacità di interagire efficacemente con gli esperti dei diversi settori applicativi, al fine di coordinare progetti relativi a software basato su intelligenza artificiale;
  • Capacità di supervisionare collaboratori, coordinare e partecipare a gruppi di progetto di prodotti basati sull’AI, e di pianificare e condurre la formazione su tematiche di AI;
  • Capacità di interagire efficacemente con gli esperti dei diversi settori applicativi, al fine di comprendere le specifiche esigenze di progetto relative ai moduli di AI ed alla loro interazione con gli utenti ed i processi interessati;
  • Capacità di analizzare, progettare e verificare le funzionalità e le prestazioni di sistemi di Intelligenza Artificiale;
  • Capacità di sviluppare tecnologie basate su intelligenza artificiale e di descrivere in modo chiaro e comprensibile le soluzioni e gli aspetti tecnici adottate utenti finali e agli organi decisionali;
  • Capacità di comprendere le funzionalità richieste dai vari moduli di una applicazione di intelligenza artificiale e di integrare tali moduli in modo armonico all’interno dell’applicazione;
  • Capacità di eseguire test specifici per la valutazione delle applicazione di intelligenza artificiale e la verifica di proprietà richieste per il loro utilizzo.

Sbocchi occupazionali
Le conoscenze avanzate fornite dal CdS consentono all’Artificial Intelligence Specialist di trovare occupazione presso industrie operanti negli ambiti della produzione software, imprese operanti nell'area dei multimedia, imprese di servizi e per la sicurezza, imprese operanti nella salvaguardia dell'ambiente e nel turismo, nella Pubblica Amministrazione, in imprese operanti nel commercio, distribuzione e logistica, imprese ed enti che operano in ambito sanitario, enti assicurativi o banche, in industrie per l'automazione e la robotica, oppure operare come liberi professionisti.

 



Quality Assurance

The quality of a degree programme is the extent to which it achieves its educational objectives and meets the quality requirements of the educational activities offered, which are determined in line with the needs and expectations of students and representatives of the world of work.

This programme has adopted a teaching Quality Assurance system in line with the University’s quality assurance guidelines and based on the e ANVUR national quality assurance guidelines, by carrying out the following activities:
  • periodic consultations with representatives of the world of work to assess the adequacy of the cultural and professional profiles offered in their courses;
  • design of educational contents and planning of resources;
  • organisation of educational activities and teaching services;
  • monitoring the effectiveness of teaching and planning measures to improve teaching and services;
  • provision of complete and up-to-date information on its website, relating to the programme (professional roles, expected learning outcomes, learning activities).
The above activities are scheduled and interrelated, based on the PDCA principles (Plan, Do, Check, Act).
schema_qualita

In a Quality Assurance system, students play a fundamental role: each student can play their part by participating in the Quality Assurance groups of their degree programme and in the Faculty-Student Joint Committees or, more simply, by taking part in the Student Survey on teaching, or questionnaires. It’s in this context that specific workshops for student representatives (‘Laboratori di rappresentanza attiva’) are periodically made available to students by the University and the University’s Quality Assurance Board. To find out more, please see the relevant section.

Il sistema di valutazione universitario e il ruolo dello studente

by Prof. Graziano Pravadelli: a lecture recorded on the occasion of the January 2021 workshop for student representatives.

QA bodies

QA in degree programmes

QA activities

Degree Programme description and regulations

symbol pdf-document

Not yet available

The Degree programme teaching regulations, published on june/july set out the organisational aspects of the degree programme, in line with the University’s teaching regulations. It includes general information about the programme, links to the relevant module web pages and specifies the administrative aspects.

Other Rules

To view other regulations of interest refer to the section: Statute and regulations

The Italian University system

schema_qualita

First-cycle degrees: Bachelor’s degree programme

First-cycle degrees are aimed at enabling students to achieve a command of general scientific methods and content, and to acquire specific professional knowledge.
Admission requirements: secondary school diploma after completing 13 years of study in total and passing the relevant State examination, or equivalent foreign qualification; admission may be subject to further assessment.
Duration: three years.
Graduation: in order to obtain the degree, it is necessary to gain at least 180 CFU; doing an internship and preparing a dissertation/thesis may also be required. Upon completion of a Bachelor’s degree, graduates may continue their studies by enrolling in a Master’s degree or other second-cycle degree programmes and courses.
Academic title: upon completion of a Bachelor’s degree (Laurea), graduates are awarded the title of “Dottore”.

Second-cycle degrees: Master’s degree

Second-cycle degrees aim to provide students with an advanced training and knowledge to take on highly-skilled roles.
Admission requirements: applicants must hold a Bachelor’s degree, or a foreign equivalent qualification; curricular admission requirements for each course may vary depending on each University.
Duration: two years.
Graduation: in order to obtain the degree, it is necessary to gain at least 120 CFU, as well as preparing and presenting a dissertation/thesis.
Academic title: upon completion of a Master’s degree (Laurea Magistrale), graduates are awarded the title of “Dottore magistrale”. Single cycle/Combined Bachelor+Master’s degrees
Some courses (Medicine and Surgery, Veterinary Medicine, Dentistry and Dental Prosthetics, Pharmacy and Industrial Pharmacy, Architecture and Building Engineering-Architecture, Law, Primary Education) are offered as Single cycle/Combined Bachelor+Master’s degrees (Corsi di Laurea Magistrale a Ciclo Unico).
Admission requirements: applicants must hold a secondary school diploma or equivalent foreign qualification; admission is subject to passing an admission test.
Duration: five years (six years and 360 CFU for Medicine and Surgery, and Dentistry and Dental Prosthetics).
Graduation: in order to obtain the degree, it is necessary to gain at least 300 CFU, as well as preparing and presenting a dissertation/thesis. Upon completion of a Single-cycle degree, graduates may continue their studies by applying for a PhD programme (Dottorato di Ricerca) or other third-cycle courses.
Academic title: upon completion of a Master’s degree (Laurea Magistrale), graduates are awarded the title of “Dottore magistrale”.

Third-cycle degrees

PhD programmes: these courses enable students to gain reliable methodologies for advanced scientific research through innovative methodologies and new technologies, and generally include internships abroad and lab activities at research laboratories. Graduates wishing to apply for a PhD programme must have a Master’s degree (or a foreign equivalent qualification) and pass an open competition; PhD programmes have a minimum duration of three years. In order to complete the programme, students must produce a research thesis/dissertation and present it at a final examination.
Academic title: upon completion of a PhD programme, students are awarded the title of “Dottore di ricerca”, or “PhD”.
Postgraduate specialisation courses: these are third-cycle courses aimed at enabling students to develop advanced knowledge and highly-specialised skills, such as in the medical, clinical and surgical fields. To be admitted to these courses, applicants must have a Master’s degree (or a foreign equivalent qualification) and pass an open competition. Postgraduate specialisation courses may last from two (120 CFU) to 6 years (360 CFU) depending on the type. Academic title: upon completion of this programme, graduates are awarded a “Diploma di Specializzazione”.

Professional Master’s programme

1st-level Professional Master’s programmes: these courses enable students to further enhance their scientific knowledge and professional skills. In order to apply, applicants must have a Bachelor’s degree, or foreign equivalent qualification. The minimum duration is one year (60 CFU). Please note that completing this course will not provide you with direct access to a PhD programme (Dottorato di Ricerca), or other third-cycle courses, as these courses are run and managed by each University at the local level. Upon completion of this programme, students are awarded a “Master universitario di primo livello”.
2nd-level Professional Master’s programmes: these courses enable students to further enhance their scientific knowledge and professional skills. In order to apply, applicants must have a Master’s degree, or foreign equivalent qualification. The minimum duration is one year (60 CFU). Please note that completing this course will not provide you with direct access to a PhD programme (Dottorato di Ricerca), or other third-cycle courses, as these courses are run and managed by each University at the local level. Upon completion of this programme, students are awarded a “Master universitario di secondo livello”.

Other useful things

Crediti Formativi Universitari (CFU/ECTS credits): Italian university courses are based on the CFU system. 1 CFU is equal to 25 hours of study. The average annual academic workload for a full-time student is generally assumed to be 60 CFU. CFU and ECTS credits serve the same purpose and generally have the same value.
Degree class: Bachelor's and Master's degree programmes that have the same learning objectives and activities are grouped into “degree classes". The educational content of each programme is set autonomously by each university; however, universities are required to include certain educational activities (and the corresponding number of CFU credits) set at the national level. These requirements are established in relation to each degree class. Degrees in the same class have the same legal value.
Double/Joint degrees: the Italian universities may establish degree programmes in partnership with other Italian or foreign universities. Upon completion of these courses, graduates are awarded a joint or double/multiple degree, one from each Partner University.

Why Verona