Study Plan - Bocconi University

This program has a strong methodological approach. Students learn solid method-based knowledge that will remain relevant as technology advances. At the same time, they are also exposed to a practical approach, gaining the ability to design and build large software systems, specifically state-of-the-art machine learning systems and intelligent systems. These abilities are acquired in project-based courses.

Coursework is also interdisciplinary. This allows students to gain an awareness of the applications of computing technologies in other disciplines where such technologies have a large impact, taking advantage of Bocconi’s other areas of expertise, including finance, economics, public policy, accounting, management and law.

Core mathematics and computer science methods

1 out of 2:

Mathematical Methods in Computer Science
Analysis of algorithms and data structures

Core courses

Algorithms for optimization and inference
Software engineering
Deep Learning and Reinforcement Learning
Information theory

Machine learning applications

Computer vision and image processing
Language technology
Machine learning lab

Seminar

AI ethics seminar

Foreign language (lessons only)

In the first year, students have the chance to participate in preparatory courses to bridge any gaps they may have and choose from two courses depending on their previous studies. In other courses, they gain an in-depth understanding of core mathematics and computer science methods and examine core machine learning applications. They also participate in an ethics seminar.

Semester 1

AI ethics seminar	2
1 out of 2 bound choice courses: Mathematical Methods in Computer Science Analysis of algorithms and data structures	8
Algorithms for optimization and inference	8
Software engineering	8

Semester 2

Deep Learning and Reinforcement Learning	8
Information theory	8
Computer vision and image processing	8
Language technology	8
Machine learning Lab	2
Foreign language - Preparatory course (elementary)	-
Total credits points of the first year	60

Computer science methods and applications

3 out of 4:

Cryptography and security
Complex systems and physical models
Computational Neuroscience
Bio-informatics

Complementary disciplines

1 out of a short list from Bocconi list:

Time Series analysis of economic-financial data
Blockchain and crypto assets
Advanced Microeconomics
Fintech and machine learning for finance
Introduction to partial differential equations"
1 elective

Foreign language

Internship

Thesis

In the second year, students delve into other computer science methods and applications and broaden their perspective through complementary disciplines. They are also encouraged to study abroad or participate in an internship abroad.

Foreign language	4
3 out of 4 bound choice courses: Cryptography and security - 1st sem Complex systems and physical models - 2nd sem Computational Neuroscience - 1st sem Bio-informatics - 2nd sem	18
1 out of a short list* from Bocconi list: Time Series analysis of economic-financial data Blockchain and crypto assets Advanced Microeconomics Fintech and machine learning for finance Introduction to partial differential equations	6
Open choice course from Bocconi list	6
internship	8
thesis	18
Total credits points of the second year	60
Total credits points	120

Please note that the program structure is subject to change.

The study plan requires one European Union language.
More specifically:

Italian for non-Italian native speakers
French, Spanish, German for Italian native speakers

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To search and get more information on the content of the various courses, browse the description of courses taught in 2023-2024.