Program Structure
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.
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.