Guides to the university

The BSc in Mathematical and Computing Sciences for Artificial Intelligence - taught in English - aims at preparing graduates who are capable of understanding and using fundamental mathematical, computational, and modelling methods and who are capable of combining them with Artificial Intelligence methods (for example: machine learning, neural networks and logic programming).

The program has an interdisciplinary nature: the basic courses that are typical of the studies in Applied Mathematics are paired with the basic courses in Computing Sciences, both theoretical and applied. Physics and Economics provide the basic examples of modelling and problem solving. Moreover, the methodological pillars of Artificial Intelligence represent the unifying element of the program, since they are gradually introduced in many courses in a coordinate way.

The main purpose of the program is to prepare graduates with solid methodological bases, who can continue their studies in Applied Mathematics or in Artificial Intelligence, or opt for different fields while having acquired the knowledge of the tools of mathematic modelling and of the basic techniques related to Artificial Intelligence. This is a basic methodological program “for” Artificial Intelligence, and not yet an advanced program “in” Artificial Intelligence.

The program focuses on critical and methodological aspects, to avoid an obsolescence of the acquired abilities.

In particular, the specific qualifying goals of the degree are:

1.    to give a rigorous theoretical preparation, in terms of contents and methods, in the fields of mathematics (mathematical analysis, algebra, geometry, probability, statistics, optimization, numerical calculus) and computing sciences (programming, algorithms, theoretical computer science, logical structures, methods for information management, algorithms on graphs);

2.    to give a rigorous theoretical preparation, in terms of contents and methods, in basic physics and in its modelling techniques (including mathematical methods for the modelling of classical and quantum systems, and for statistical physics), and in basic economics and in its  modelling techniques (including game theory, decision theory, and behavioural modelling);

3.     to give a basic methodological preparation in Artificial Intelligence (machine learning, continuous and discrete optimization in high dimensions and in the associated computational techniques, neural networks, elements of logic programming); 

4.     to teach how to master the main mathematical, computational, modelling and Artificial Intelligence methods for the solution of quantitative problems of different degrees of complexity, using multiple tools and constructing adequate models;

5.    to develop soft skills such as effective communication and ability to work in a team, via in class / out of class activities linked to the curricular courses; and to develop, via ad hoc seminars, further abilities which can be useful on the job market, such as the ability to evaluate the ethic and social impact of issues connected with Artificial Intelligence, sciences, and technologies and the ability to discuss and analyse in detail (also in a specific applied setting) selected Artificial Intelligence issues;

6.       besides English (the teaching/learning language of the degree), to promote the knowledge of another EU language (Italian is compulsory for students who are not Italian native speakers).