Computer Science

This course is part of the LM degree program and is intended for advanced level students. Enrollment s by consent of the instructor. This course discusses theoretical foundations, computational properties, and use cases for some of the most popular supervised and unsupervised machine learning techniques. In particular, the course addresses tasks such as classification, clustering, and discovery of rules by using modern machine learning methods and libraries.

This course is part of the Laurea Magistrale program. The course is intended for advanced level students only. Enrollment is by consent of the instructor. The course focuses on relevant research themes related to peer-to-peer systems, blockchain technologies, cryptocurrencies and novel applications that can be built over the blockchain. Nowadays, the most prominent peer-to-peer systems are related to the blockchain and distributed ledgers. Thus, the main part of this course is devoted to these topics. Bitcoin and novel cryptocurrencies gathered momentum in the last months. More and more investors look with interest to these technologies, while others label them as a dangerous speculative bubble. The truth is that the blockchain, and the alternative implementations of a distributed ledger, represent very interesting technologies, that can be exploited to build novel distributed applications. The underlying building blocks are related to many concepts and research areas of computer science in general. This course illustrates the main principles and conceptual foundations of the blockchain and the Bitcoin network. Topics covered: Introduction to peer-to-peer systems; Overlay topologies and decentralization; Introduction to Crypto and Cryptocurrencies; The blockchain: how to achieve decentralization; Transactions and transaction scripting languages; Mining; Attacks to the blockchain; Anonymity; Smart contracts.

The course is designed to prepare students for leadership in a globally interdependent and culturally diverse workforce. Throughout the course, students are challenged to question, think, and respond thoughtfully to the issues they observe and encounter in the internship setting, and the designated city in general. Students have the opportunity to cultivate the leadership skills as defined by the National Association of Colleges and Employers (NACE), such as critical thinking, teamwork, and diversity. Assignments focus on building a portfolio that highlights those competencies and their application to workplace skills. The hybrid nature of the course allows students to develop their skills in a self-paced environment with face-to-face meetings and check-ins to frame their intercultural internship experience. Students complete 45 hours of in-person and asynchronous online learning activities and 225-300 hours at their internship placement.

This class offers an introduction to the fundamental concepts of distributed systems. Topics include: synchronization; distributed algorithms; distributed architecture; distributed file systems; end-to-end systems (P2P); distributed transactions.