Master Meetings

Have you decided on which Master programme to study? Would you like more information on the contents and teaching methods at USI? Register at our Master Meetings to attend courses.
The various Master Meetings offer you the opportunity to follow lectures together with the current master students. Guided by a USI student, you can visit the campus and make up your mind as to whether the contents correspond to your study ambitions.

Please find here below the entire programme.

Registration is compulsory. Please register online.

23.11.2021

MSc in Artificial Intelligence

08:30 - 10:00
C1.03, East Campus

Distributed Algorithms
Prof. Fernando Pedone

Course objectives
Distributed computing systems arise in a wide range of modern applications. This course surveys the foundations of many distributed computing systems, namely, the distributed algorithms that lie at their core. The course provides the basis for designing distributed algorithms and formally reasoning about their correctness. It addresses issues related to what distributed systems can and cannot do (i.e., impossibility results) in certain system models.
Course description
The course focuses on three aspects of distributed computing: system models, fundamental problems in distributed computing, and application of distributed algorithms. System models include synchronous versus asynchronous systems, communication models, and failure models. Several fundamental problems are covered, including consensus, atomic broadcast, atomic multicast, atomic commit, and data consistency. Applications of distributed algorithms target various forms of replication techniques.

10:30 - 12:00
D1.14, East Campus

High-Performance Computing
Prof. Olaf Schenk

Course objectives

Are you interested in using Europe’s faster supercomputers (and getting ECTS credit points for doing so)? Would you like to learn how to write programs for parallel supercomputers, such as a Cray or a cluster of GPUs? The course is designed to teach students how to program parallel computers to efficiently solve challenging problems in science and engineering, where very fast computers are required either to perform complex simulations or to analyze enormous datasets.

Course description

The goal of the HPC course is that students will learn principles and practices of basic numerical methods and HPC to enable large-scale scientific simulations. This goal will be achieved within six to eight mini-projects with a focus on HPC, CSE, and AI. The content of the course is tailored for 1st year Master students interested in both learning parallel programming models, scientific mathematical libraries, and having hands-on experience using HPC systems.

14:30 - 16:00
C1.03, East Campus

User Experience Design
Prof. Marc Langheinrich, Dr Monica Landoni

Course objectives

This class aims at familiarising students with both the theory behind the discipline of Human Computer Interaction (HCI) and the practical process of User eXperience (UX) design.

Course description

Usability and the overall User Experience are crucial for the success of any digital product. This course takes a hands-on approach in teaching how to create useful, usable, and (well-)used digital products. Students not only develop an awareness and appreciation of the crucial implications of good interfaces in terms of overall system performance and user satisfaction, but also learn core skills needed in order to identify user requirements, envision interfaces and processes, and evaluate competing design options.