Liste des cours proposés par spécialisation pour l’année académique 2021-2022
Liste des cours proposés par spécialisation pour l’année académique 2021-2022
L’inscription à une spécialisation se fait dans l’onglet “Inscription aux cours” sur IS-Academia.
Délai d’inscription pour la spécialisation = début du 3ème semestre des études Master (M3).
La spécialisation est un ensemble de cours permettant aux étudiant·es d’approfondir un aspect particulier de leur discipline principale. Elle leur offre ainsi l’opportunité de développer une expertise dans un domaine précis issu de leur cursus Master.
Les étudiant·es IN et SC peuvent choisir une spécialisation ou un mineur. Les étudiant·es Cyber et DS ne peuvent pas s’inscrire à une spécialisation.
Il n’est possible de s’inscrire qu’à une seule spécialisation.
Une spécialisation correspond à 30 ECTS, qui doivent être acquis pendant la durée des études de Master et sont obtenus uniquement parmi les branches listées dans la spécialisation choisie. Ces 30 crédits sont comptabilisés parmi le Groupe 1-core courses et/ou le Groupe 2-options du plan d’études du Master .
Les cours Bachelor qui figurent dans une spécialisation et ont déjà été validés pour le Bachelor ne peuvent pas être pris à nouveau au Master, ni être comptabilisés pour la spécialisation.
La spécialisation est mentionnée dans le supplément au diplôme.
Liste des spécialisations 2021-2022
(texte en anglais seulement)
Computers started off more than half a century ago as huge machines occupying entire buildings before reaching everyone’s desks, firstly in the form of desktop PCs and more recently of slim and powerful laptops and PDAs. Yet, all these pervasive devices constitute only a minimal part of the computers which surround us: tens or even hundreds of processors, the hearts of every computer, populate now our houses and are embedded in objects as diverse as our cars, our mobile phones, our DVD players, our broadband modems, our high-definition televisions, and our cameras. Computer Engineering is the science of making these extremely complex systems possible and tackling the multitude of related challenges: Computer Engineering studies how to design them quickly and with ever increasing computational power, so that they can in turn enable breathtaking progress in applications. Computer Engineering is the art of conceiving electronic systems which are sufficiently cheap and power-effective to be economically viable and still fit for their purpose. Computer Engineering is the craft of programming these devices efficiently and effectively while guaranteeing that they will operate correctly under every predictable circumstance. The Computer Engineering specialization is designed to help students build a solid and durable background in this quickly growing area. Developing successful products requires a clear understanding of concepts as diverse as operating systems and VLSI electronics, processor architecture and discrete optimization, compilers and design technology. Good development managers need to anticipate new technological breakthroughs and to be capable of reinventing continuously system design concepts. Research in Computer Engineering is also extremely active: as systems become more complex and companies need to deploy new products faster, research helps pushing design automation further. Successful students in the Computer Engineering specialization are intrigued by the multifaceted complexity of real systems; they are curious of both hardware and software challenges, and are fascinated by the potentials of envisioning completely new devices which are made possible by the joint progress of electronics and computer and communication sciences.
We are witnessing the explosion of data from an increasingly broad set of sources: smartphones, web services, social networks, online finance, smart buildings, transportation systems, environmental monitors, Internet of Things (IoT), and many other sensors. Many of these data streams are byproducts of human activity, and are not structured (or relational), but instead unstructured, noisy, and “rich” (e.g. pictures, videos, mobility patterns, text messages). The goal of Data Science is to extract reliable knowledge and accurate predictions from such large-scale, diverse, noisy, and often unstructured data. This interdisciplinary field lies at the intersection of statistics, computer science, and specific application domains, and draws on machine learning, artificial intelligence, signal processing, high-performance computing, data management, and visualization. Data Scientists possess the models and tools to explore new data sources, often in collaboration with domain experts, to build statistical models, and to develop inference and prediction algorithms that extract value from the raw data. DS is becoming increasingly central in many areas of the economy, such as in digital and social media, mobile, finance, pharma and health care, transportation, advertisement, robotics, and surveillance. The challenges and opportunities for society and business are huge and evolving quickly, and Data Scientist is considered one of the hottest career profiles today.
Foundations of Software develops the scientific and technological basis of programming. Its objects of study are everything one needs to build software of high quality including algorithms, programming notations, means to verify system properties via type systems, model checking, or other static analyses, testing or advanced cimpilation techniques. The specilalization is hence at the very core of the software industry; it should be ofinterest to everyone who wants to become a better software engineer, independently of a specific application area. Typical employment profiles are advanced software engineering positions which require algorithmic thinking, problem solving capabilities, and a solid engineering approach to quality assurance.
The current proliferation of electronic communication affects all layers of society. For all parties involved in all stages of the design and life cycle of data processing tools, this brings along huge responsibilities with respect to the protection of those data. Thus, there is a growing demand for Information Technology engineers with a specialization in Information and Communication Security both in the public and private sector, ranging over a wide variety of industries, but with a focus on the financial sector.
Students in Information and Communication Security should be prepared to address a broad range of subjects, corresponding to the issues involved in information protection. Examples are the mathematically and algorithmically inclined underlying cryptographic and cryptanalytic techniques, design of secure hardware, networking protocols and security, biometric authentication mechanisms, media content protection, but also a thorough understanding is required of the softer issues involved, such as human interfaces and security management. All these aspects are the subject of very active and deep research to address the many remaining challenges, and create tremendous opportunities for a successful career in industry or academia.
Every day, we use the Internet or mobile network to communicate, send emails or SMSs, chat with MSN or Skype, watch videos over YouTube or a mobile phone, use blogs to express political opinions, etc. In the future, the “Internet of things” will allow sensors and objects of all kinds to communicate; this will be a key enabler for energy and water savings. All of this may happen because, behind our ADSL line or Nokia phone, there are networks and people running them.
In the Networking and Mobility specialization we learn to master the theory, tools, and practice that are supporting web and mobile services. Challenges are in scale, complexity, reliability, security, and operation. Mastering networks requires understanding the architectural principles upon which they are built and the ability to experiment with them. Jobs concerned with this specialization are with Internet service providers, mobile network operators, large corporations, public services and the government, and consulting companies. The traditional applications are today with people-to-people communication (web, email, telephone, etc.) and will in the future concern the optimization of usage of natural resources. Jobs are typically in management of network or information services and in research or development. Products range over a very broad spectrum, from devices to services and consulting. The area is growing, in particular in the domain of the “Internet of things”. Applications to security, resource management and reliable operation are of particular interest. Students should have a well balanced set of skills, combining logical thinking, a sense of organization, and some mathematical and programming skills.
The field of Signals and Images stands at the intersection of disciplines such as sensing systems, communications, human and artificial vision, speech and language processing, biomedical systems, computer graphics, machine intelligence, virtual reality, colour imaging and art. Thanks to the advances in the field, computers become smarter and are able to execute tasks previously only performed by human beings (speech recognition, identification of signatures, airplane navigation systems, robot-driven surgery, etc.). The present specialization is of primordial importance in fields where new devices and services are being developed-e.g., robotics, surveillance, GPS-based guiding systems, biomedical systems, home entertainment, video and cinema equipment, digital photography, and security. Thanks to advances in algorithms, methods, and devices, the field continues to evolve.
Smart scientists and engineers mastering this field are needed both in Switzerland and around the world. Students interested in combining modelling and computational approaches to solve theoretical or real-world problems should be interested by the offered courses. The tools and methods they will acquire will allow them to become active in the field, both in research and in advanced engineering.
A modern computer system spans many layers: applications, libraries, operating systems, networks, and hardware devices. Examples of such computer systems include the iPhone, Facebook, the Mars Rover, online banking, airplane flight controllers, and most modern medical devices. Building a good system entails understanding how hardware and software interacts, making the right trade-offs (e.g., between performance, durability, and correctness), and understanding emergent behaviors. The difference between great system designers and average ones is that the really good ones make design trade-offs in a principled fashion, not by trial-and-error. In the Systems specialization, students learn how to solve problems in computing by building a suitable computer system, based on ideas, techniques, and algorithms from operating systems, networks, databases, programming languages, and computer architecture. The specialization includes basic courses on these topics, which teach how the elemental parts of modern systems work, and it culminates with the Principles of Computer Systems course, which distills out of the basic courses several key principles underlying successful system design.
The last decade has witnessed a communications revolution. We now expect to be connected anytime and anywhere, and ever increasingly this means wireless. Furthering this trend is the connectivity of not just people but of devices-only in the last four years, 4 billion wireless devices have been sold. In contrast to the wish that wireless should “just work\
Starting from the pioneering work of Alan Turing, theoretical computer science (TCS) has largely evolved in an attempt to mathematically understand what computational models can and cannot do. Initial motivations were “computational” problems arising from various scientific disciplines – e.g. How to break codes? How to simulate differential equations? How to sequence the (massive) human DNA?
In a short span, it has matured significantly, has seen remarkable success on several of its foundational questions. Attempts to tackle questions such as « Is P = NP’ » and « How to handle the explosion of data?’ » have inspired ground-breaking results (such as the PCP Theorem and near-linear time algorithms for solving linear system of equations.) These results have built on (and contributed to) large bodies of mathematical techniques from information theory, mathematics, optimization and statistics.
These efforts are also resulting in unexpected, but perhaps inevitable,payoffs: as it stands today with its models, tools and mathematical techniques, TCS is fast becoming a powerful lens to view nature and society. Several fundamental problems in biology, economics, physics and social sciences are inherently computational and can be, and are being, tackled by theory. Thus, TCS has assumed a unique and exciting position with a potential to deepen the “understanding” of the world we live in by viewing the basic processes in this universe e.g. evolution, behavior, laws of physics, as computing something.
The goal of this specialization is to train students rigorously in the foundational areas such as algorithms, complexity theory and optimization and also expose them to the state of the art and application areas.
Almost all computing devices are connected through the Internet. The openness of the Internet, whose participants cannot be controlled by central authorities, poses novel computer science challenges for resource control, security, programming, data distribution, and information access. As an open information exchange platform, the Internet is transforming many sectors of today’s society and economy, including business, commerce, engineering, medicine, and media. This changes the face of established enterprises and creates new business opportunities for start-ups, both leading to a high demand and many exciting career opportunities for experts with a background in Internet Computing. A key asset for such experts is interdisciplinarity linking a strong technical background with the openness to develop new and innovative concepts in cooperation with users.