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.

sportello in presenza: martedì, giovedì e venerdì, dalle 10:00 alle 13:00.

sportello online: lunedì, martedì, mercoledì e giovedì, dalle 14:00 alle 17:00.

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.

The Single Annual Record (SUA-CdS) is the identity card of each degree program, published on the Universitaly portal to present the educational offerings of all Italian universities. Each year the CdS Referent updates its contents so that they are consistent with what is offered within the Course.

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
  • S.T.E.M. course Yes
  • Degree class LM-18
  • Location VERONA
  • Language English
The aim of the Master's degree course in Artificial Intelligence is to enable students to acquire the multidisciplinary knowledge and skills necessary for the effective application of computer skills in the field of artificial intelligence and its disciplines. Students are expected to acquire solid skills in the fields of computer science and engineering, with particular emphasis on methods based on "symbolic" representations of problems, i.e. representations that use and manipulate symbols, such as representations based on logic, and state-space search methods; methods based on probabilistic representations, typical of data-driven machine learning; artificial intelligence methods whose decisions can be understood by humans, in line with the current strong trend towards regulation of artificial intelligence for applications involving autonomous agents and humans.
This knowledge will be supported by in-depth studies in other disciplines aimed at developing learning paths concerning: the development of mathematical models and the solving of optimisation problems; the use of principles and sources of law concerning the management of artificial intelligence tools; the development of applications in the economic and financial spheres; knowledge of the ethical bases for the management of artificial intelligence technologies in the production context and in relation to the interpretation of socio-economic phenomena connected with it.
In particular, the following specific training objectives have been identified
- a consistent theoretical and practical basis on machine learning and deep learning that provides the student with the basics and the state of the art in the field;
- a consistent theoretical and practical basis on planning and scheduling, i.e. symbolic and constraint programming, which are the foundations of classical AI;
- a consistent theoretical and practical basis on reinforcement learning elements for the design of adaptive artificial intelligence systems;
- a substantial theoretical and practical basis on elements of advanced programming for AI in order to provide students with the foundations for the design, assembly and deployment (e.g., on the cloud) of software architectures aimed at AI;
- a consistent theoretical and practical basis on methods for the study, analysis and evaluation of cooperation between agents, in this case AI algorithms and human operators;
- methodological-operational aspects of mathematics, statistics, physics, law and ethics relating to AI problems;
- An understanding of the impact of artificial intelligence solutions in the social context;
- Knowledge of one's professional and ethical responsibilities;
- The knowledge of basic cognitive tools for the continuous updating of one's knowledge.
All this knowledge will aim to enable students to be able to develop complex methods, tools and technologies based on artificial intelligence in various application areas.
These objectives provide the cultural, scientific and technical foundations of the Artificial Intelligence graduate and take into account the requirements that have emerged from the meeting with stakeholders.

The courses are organised over the two years so as to ensure proper sequencing in the acquisition of concepts. In particular, knowledge related to the theoretical foundations of Artificial Intelligence is provided in the first year courses. More specific knowledge concerning advanced techniques, specific applications of Artificial Intelligence and related activities are provided in the second semester of the first year and in the second year. The harmonisation of teaching content is supported by the presence of laboratories that integrate different knowledge and application skills, and are designed to develop application, interpersonal and team-working skills. The workshops also serve as preparation for the apprenticeship. The harmonisation of content is supported by the presence of applied and by nature interdisciplinary examinations. In the second year the student is also required to undertake a training and orientation placement.

JOB PROFILES

ARTIFICIAL INTELLIGENCE SPECIALIST

Function in a work context:
Holds roles such as the coordinator of artificial intelligence projects, the analyst of software with artificial intelligence capabilities, the developer of software modules with artificial intelligence capabilities, the integrator of such modules or the verifier of such modules. In general, the AI Specialist takes on roles of responsibility in the design and development of artificial intelligence methods and tools to create systems capable of autonomously acquiring knowledge and developing models and strategies. Examples of such systems are: systems for knowledge management and knowledge extraction from large amounts of data (e.g., social networks, internet); artificial intelligence systems for the film and video game industry; AI systems for extracting, managing and processing data related to environmental monitoring and climate change; AI systems for economics and finance; AI systems for sustainable growth (e.g., "smart building", "smart cities", "smart grids"); AI systems for medicine (e.g., diagnostics, tele-medicine); AI systems for the product and service industry (e.g., "AI-assisted programming", automatic text and speech translation, cybersecurity, autonomous robots, assisted and autonomous driving systems).

Skills associated with the function:
- Ability to interact effectively with experts in different application areas in order to coordinate projects related to artificial intelligence-based software;
- Ability to supervise collaborators, coordinate and participate in AI-based product project teams, and to plan and conduct training on AI topics;
- Ability to interact effectively with experts in different application fields in order to understand the specific project requirements related to AI modules and their interaction with the users and processes involved;
- Ability to analyse, design and verify the functionality and performance of AI systems;
- Ability to develop AI-based technologies and to describe the solutions and technical aspects clearly and comprehensibly to end users and decision-makers;
- Ability to understand the functionality required by the various modules of an artificial intelligence application and to integrate these modules harmoniously within the application;
- Ability to perform specific tests for the evaluation of artificial intelligence applications and the verification of properties required for their use.

Employment opportunities:
The advanced knowledge provided by the CdS allows the Artificial Intelligence Specialist to find employment in industries operating in the areas of software production, companies operating in the multimedia area, service and security companies, companies operating in environmental protection and tourism, in the Public Administration, in companies operating in commerce, distribution and logistics, companies and entities operating in the health sector, insurance companies or banks, in industries for automation and robotics, or to work as a freelancer.



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

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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 Regulations

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