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.

Next appointment: 21-25 November 2022.

Registration form

23.11.2022  

8:30-10:15
Room C1.05
East campus

Algorithms & Complexity

Algorithms are fundamental to computer science and they lie at the core of any software system. This course will cover fundamental techniques for designing efficient computer algorithms, proving their correctness, and analyzing their performance. It will also cover several application problems that use these techniques. Students will encounter a variety of problems and techniques; the objective is to learn algorithmic foundations of computer science and acquire the ability to design correct algorithms on their own.

8:30-10:15
Room D1.13
East campus

Mobile and Wearable Computing

The widespread use of mobile and wearable devices enables the implementation of novel services in applications areas like, e.g., mobile health, sustainability, smart working, and more. This course introduces the building blocks of such services and discusses the challenges that arise on the path towards their realization. Specific topics covered include: hardware platforms; programming environments and tools; the collection and processing of sensor data; the design of mobile user interfaces; local and remote data storage; privacy and security issues. In addition to theoretical concepts, the course also includes Android programming tutorials as well as tutorials showing how specific sensor data (e.g., heart rate data) can be collected, processed, and used to enable services and applications. A programming project accompanies the course and allows students to put in practice both the theoretical and programming concepts learnt in the classes and tutorials. 

10:30-12:15
Room D1.14
East campus

High-Performance Computing

The goal of the HPC course is that students will learn the 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. The course will be offered online as well to also allow double-degree Master students and EUMaster4HPC master students to enroll.

14:30-16:15
Room C1.04
East campus

User Experience Design

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.

14:30-16:15
Room D1.14
East campus

Software Design & Modeling

The main focus of the course are object-oriented design mechanisms, but with some topics targeting functional programming. After an introductory recap of object-oriented programming, the course discusses how to assess the design quality of object-oriented systems, how to identify and use so-called design patterns, how to avoid common design flaws, and how to introduce rigorous yet practical means of documenting design and functionality.

14:30-16:15
Room D1.15
East campus

Software Performance

This course teaches how the various layers of a computer system interact and affect the resulting performance. It performs two cuts down the system stack: one about the 'state' and the other about the 'behavior' of a system. The discussion of 'state' investigates memory usage of applications, leak detection, garbage collection, virtual memory management, and cache performance. The discussion of 'behavior' investigates call graphs, dynamic class loading, shared libraries and dynamic linking, control flow graphs, exception handling, compiler optimizations, and branch prediction.

16:30-18:15
Room C1.05
East campus

Machine Learning

This course covers basic and advanced theory and methods of Machine Learning. From this wide field, we focus on neural networks, probabilistic models, and reinforcement learning in both theory and practice. Students will solve theoretical exercises and perform programming tasks; after just a few lectures, they will be able to implement a neural network which performs image classification better than any other known method. The intention of this course is to lay a solid groundwork for the student, such that he/she will be able to understand advanced state-of-the-art methods, to skillfully use diverse methods to solve practical problems, and to properly interpret results.

16:30-18:15
Room D1.14
East campus

Artificial Intelligence

The aim of the course is to present the most modern techniques for solving complex problems. We focus on state of the art meta-heuristic for continuous function and combinatorial optimization: among the methods we deepen simulated annealing, genetic algorithms, variable neighborhood search and ant colony optimization. Gaming with two players will be also discussed as the integration between meta-heuristics and machine learning. Students are asked to implement and test some of these techniques.