GUIDES TO THE UNIVERSITY

Program Director:

Carlo BALDASSI

Assistant to the Program Director:
Guido Osimo

Field of study:
Mathematics (no. L-35 Ministerial Decree 16 March 2007; the program benefits from the “flexibility” allowed by art. 8.1 MD 6/2019).

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).

Junior profile, expert in mathematical, computational, modelling and Artificial Intelligence methods

Position in the workplace:

The graduate will mainly work in a team (as an internal resource or an external consultant), possibly supporting senior managers. 

The graduate will carry out activities such as:

- collection of large amounts of data, basic data processing and analysis of the information resulting from data;

- choice and use of mathematical, computational, and modelling methods for the advanced analysis of data;

- use of Artificial Intelligence methods (for example machine learning and artificial neural networks).

These activities can be carried out in different fields such as physics and other fields of natural sciences, and economics and other fields of social sciences (e.g. finance, management, marketing, accounting, etc.).

Skills associated with the position:

The graduate has a solid mathematical and computational knowledge, a solid knowledge in modelling sciences (physics and economics), and the ability to analyse problems of various levels of complexity and to develop and creatively use methods for the understanding and modelling of complex realities. Moreover, the graduate has the necessary soft skills to promptly fit in a work context and to interact in a constructive way with the other professional profiles composing the team.

Thanks to an academic education that focuses on the critical and methodological aspects, the graduate will build on his/her multidisciplinary  background to easily adapt to new problems, rapidly acquire further specific knowledge and become capable of playing a key role in many evolving and innovative fields which require continuous knowledge update.

Career opportunities:

- Second-level studies in Artificial Intelligence, Applied Mathematics, Statistics, Data Science, Computer Science, Physics, Economics, Finance, and Business, both in Italy and abroad. Due to its methodological nature, the program allows to access also second-level studies in different fields, in which the analysis of large amounts of data and modelling play an important role.

- Main job opportunities: companies, institutions, research groups, both local and international, of various size, industry and setting (private/public), characterized by the need of using the above professional profile.

The BSc in Mathematical and Computing Sciences for Artificial Intelligence (L-35) is taught in English.

The study plan is built on four main blocks:

• extensive and in-depth preparation in mathematics and computer science (in the first two years);
• basic preparation in physics and economics (in the first two years);
• basic preparation in the mathematical and computational methods for modelling in physics and economics (in the second and third year);
• basic preparation in specific Artificial Intelligence methods (in the second and third year).

Moreover, students can select elective activities (elective courses, to be passed in Italy or abroad, internship) to adapt the last part of the study plan to their individual goals. These are meant to give students the opportunity to widen their knowledge towards other disciplinary fields that have evolved and have become a potential ground for modelling and Artificial Intelligence methods, in particular within social sciences. The study plan also includes:

• one EU language (different from English and from the student’s mother tongue); Italian compulsory for non-native Italian speakers;
• seminars to develop professional skills (e.g. digital ethics, teamwork & effective communication, Artificial Intelligence laboratory);
• final paper.

The prerequisite for enrolling in the first year 2023-2024 of the program is an English level equal at least to B2 (in accordance with European Language Framework); (see the table).

The program structure is valid for the students initially enrolled in the academic years of reference for this section.

First year of studies

Second year of studies

Third year of studies

Notes 

Modules:

• code 30539 ‘Computer Science - Module 1 (Introduction to Computer Science and Programming) and code 30540 ‘Computer Science - Module 2 (Computing Theory and Algorithms)’ are respectively the first and the second module of the course code  30538 ‘Computer Science’;
• code 30542 ‘Mathematical Analysis - Module 1’ and code 30543 ‘Mathematical Analysis - Module 2’ are respectively the first and the second module of the course code 30541 ‘Mathematical Analysis’;
• code 30551 ‘Advanced Analysis and Optimization - Module 1’ and code 30552 ‘Advanced Analysis and Optimization - Module 2’ are respectively the first and the second module of the course code 30550 ‘Advanced Analysis and Optimization’.

Courses divided into modules are officially passed (and can be recorded in the student academic career and certified) only after passing both modules’ examinations. The final grade is the grade point average of the two marks, which is the credit points for the course. The mean is rounded up if decimals are equal or higher than 5, rounded down if they are lower than 5.Credit points and grades earned for the individual modules passed are taken into account for rankings within the University (e.g. Bocconi Scholarship, selection for International Programs...) and they can be viewed by printing the unofficial academic transcript at Punto Blu.
 

Language
Detailed information on language courses can be found in "Languages and Computer skills".

Exam sequence
Detailed information on exam requirements, i.e. which exams must be taken before others and the timelines is published in the chapter on Exams.

Electives and internship
The positioning of elective courses and internship in the first or in the second semester is merely a suggestion. Students can choose how to allocate these activities along the two semesters.

For the choice of elective activities, please see the paragraph 2.1.12.5. Choice of Elective Activities.

In accordance with the educational objectives of the program and the ministerial table, "Scienze matematiche" field of study, the program structure may be subject to variations decided by the Academic Bodies.

Upon enrollment in the third year, students must choose 12 credit points ("elective activities" - 2 slots - 6 credits each) as follows:

• First slot (6 credit points) to be chosen from the “BAI basket”:
   

(*) students who opt for this course will graduate with 181 credit points

• Second slot (6 credit points) to be chosen from the "overall 3-y degree programs basket" (see chapter 2.2), which includes the “BAI basket” (activities not chosen in the first slot) or an internship.

Upon prior authorization by the 3-y degree Program Director, the educational activities included in the previous list can be replaced with educational activities passed abroad which do not have any correspondence with Bocconi courses (see 7.14 ‘Credit for Exams Passed at Universities Abroad).