Informazioni pratiche per la comunità USI

Piano degli studi Master in Informatics (MSI)

Questa pagina contiene informazioni destinate agli studenti già immatricolati.

Per informazioni generali sul Master, dedicate a tutti gli interessati, vi preghiamo di visitare la pagina:

www.usi.ch/msi

 

Piano degli studi Master in Informatics (MSI)

Il piano degli studi (o anche "piano di studio" o "piano dei corsi") del Master contiene le indicazioni sulla struttura del percorso formativo.

Il contenuto è disponibile solo in lingua inglese.

 

Expand All

  • Study plan 2022-2024

    The study programme consists of four semesters full-time study (120 ECTS). Students select 30 ECTS of foundational courses (over the two years) and 60 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

    To broaden the student's perspective, in addition to courses from the other master programmes of the Faculty, up to 6 ECTS of electives can be obtained by following any Master course offered at USI.

    The students have the possibility to obtain a specialisation by writing the Master's thesis and taking at least 18 ECTS of courses in one of the following areas:

    • Artificial Intelligence
    • Computer Systems
    • Geometric and Visual Computing
    • Information Systems
    • Programming Languages
    • Software Development
    • Theory and Algorithms

     

    FOUNDATIONAL COURSES (30 ECTS out of 36 ECTS) ECTS Sem
    Algorithms & Complexity 6 Autumn
    Distributed Systems 6 Autumn
    High-Performance Computing 6 Autumn
    Machine Learning 6 Autumn
    Software Design & Modeling 6 Autumn
    Information Security 6 Spring
         
    ELECTIVES (60 ECTS)    
    Advanced Java Programming 6 Autumn
    Advanced Topics in Machine Learning 3 Autumn
    Artificial Intelligence 6 Autumn
    Computer Aided Verification 6 Autumn
    Deep Learning Lab 3 Autumn
    Distributed Algorithms 6 Autumn
    Edge Computing in the IoT 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Numerical Algorithms 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    User Experience Design 6 Autumn
    Advanced Computer Architectures (SP24) 6 Spring
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Geometric Algorithms (SP24) 6 Spring
    Graph Deep Learning 3 Spring
    Image and Video Processing 6 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring
    Robotics 6 Spring
    Security Aspects of Machine Learning 3 Spring
    Software Analysis 6 Spring
    Software Architecture 6 Spring
    Software Quality & Testing 6 Spring
         
    Electives from other master programmes of the Faculty of Informatics    
    MSc in Artificial Intelligence    
    MSc in Computational Science    
    MSc in Financial Technology and Computing    
    MSc in Management & Informatics    
    MSc in Software & Data Engineering    
         
    MASTER THESIS (30 ECTS)    
    Master Thesis (can be started in the 3rd semester) 30 Spring

    Please be aware that slight changes in the study programme may occur.

    Specialisation in Artificial Intelligence

    A wide variety of techniques will be taught, including intelligent robotics, artificial deep neural networks, machine learning, metaheuristics optimization techniques, data mining, data analytics, simulation and distributed
    algorithms. The main courses are integrated with laboratory works where students have the possibility to use real robots and to practice with state of the art tools and methodologies.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Artificial Intelligence” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Advanced Topics in Machine Learning 3 Autumn
    Artificial Intelligence 6 Autumn
    Deep Learning Lab 3 Autumn
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Graph Deep Learning 3 Spring
    Robotics 6 Spring
    Security Aspects of Machine Learning 3 Spring

    Students graduating with this specialisation will develop a taste for working on complex problems. In their future careers, they will be able to apply their knowledge in many interdisciplinary areas including robotics, business forecasting, intelligent search, video games, music and entertainment, chat bots, medical diagnostics, self-driving cars, to name a few.

     

    Specialisation in Computer Systems

    Think of the interconnected data management systems of a global institution: a bank, an airline, or a national government. Think about the large clusters of computers used by scientists to map the human genome. Think about a networked massively multiplayer game. Think of a telecommunication network such as the Internet or the 3G mobile network. Think about computers that help drive your car safely and efficiently. These are all distributed computer systems and, like them, many others are being developed and used pervasively in our modern society. Needless to say, computers and networks play a central role within these systems. They process, store, and transmit information to support a wide variety of tasks, ranging from the safety-critical operations of a transportation system to the business-critical functions of a bank, to the performance-critical computations of the scientific models studied by physicists or molecular biologists. The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a PhD.

    The Computer Systems specialization of the Master of Science in Informatics prepares professionals capable of designing and developing modern distributed computer systems. In particular, the emphasis of the design taught is on dependability, which means that systems are engineered to withstand failures of system components and to gracefully sustain heavy workloads and/or intense communication traffic. The knowledge and technical expertise acquired in this specialization is an ideal basis for a career as a system engineer, with employment opportunities in virtually any company whose business depends on computing systems. Moreover, the analytical skills that characterize this specialization make up a versatile professional profile, as they are more generally applicable to a range of diverse problem-solving tasks.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Computer Systems” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Computer Aided Verification  6 Autumn
    Distributed Algorithms 6 Autumn
    Edge Computing in the IoT 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Advanced Networking 6 Spring
    Security Aspects of Machine Learning 3 Spring

     

    Specialisation in Geometric and Visual Computing

    The last decade has witnessed a remarkable emergence and maturing of technologies dealing with visual and geometric data. Many methods that were in the domain of research labs have become classical and standard industry practice. Think of Google Goggles (a web service allowing the user to take a street image with a mobile phone and get information about the depicted objects), Google Street View and Microsoft Photosynth (photo tourism service, based on computer vision algorithms for building 3D models of cities from very large sets of images), Microsoft Kinect (an add-on to Xbox console allowing gesture-based control, based on computer vision technology to scan the 3D scene in real-time and pattern recognition algorithms to analyze the gestures), and the movie Avatar (setting a new standard both in computer graphics realism, but also remarkable for the use of very sophisticated 3D vision technologies during production). These examples belong to the field of Geometric and Visual Computing, dealing with processing and analyzing visual and geometric information. Geometric and Visual Computing is a combination of computer science (discrete algorithms, data structures, software engineering) and mathematical modelling (theoretical foundations and computational methods), which are used in the domains of computer graphics, computer vision, 2D and 3D signal processing, and pattern recognition. The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

    Various aspects of geometric computing are required for jobs dealing with CAD/CAM systems, VLSI, geographic information systems, engineering, numerical simulations, special effects and graphics (e.g. movie industry), image processing and analysis, computer vision, and multidimensional data analysis. These jobs demand specialists combining a strong theoretical background in math, expertise in geometry, knowledge of computational methods, and software development skills.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Geometric and Visual Computing” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Graph Deep Learning 3 Spring
    Image and Video Processing 6 Spring
    Robotics 6 Spring

     

    Specialisation in Information Systems

    Students will learn how to design, develop and maintain large systems for the indexing and retrieval of all kind of information, from database records to textual information or multimedia and Web hypermedia (images, video, etc). An ICT professional requires nowadays a mix of technical know-how comprising skills such as project management, information architecture, and human-computer interaction. This specialisation is designed to address these gaps and to educate ICT professionals to play a leading role.

    The Information Systems specialisation aims at preparing students for leadership careers in the area of information systems design and development, information systems quality assurance, information systems integration and information systems project management.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Information Systems” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    User Experience Design 6 Autumn
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Data Analytics 6 Spring

     

    Specialisation in Programming Languages

    Programming languages are a medium for communicating our intentions to the computer and to each other. The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis. Programming languages is an active area. There is a great need for new programming abstractions to be developed, new languages invented, and existing languages extended to be able to effectively program and take full advantage of new platforms and architectures.

    Graduates will be prepared to work in fields related to program understanding, analysis, manipulation, and transformation. They will acquire the tools and techniques needed to specify and implement language-based solutions. Students will study fundamental aspects of programming languages, both from the theoretical and the practical side, preparing them to become industry professionals or to continue on towards a PhD.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Programming Languages” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Advanced Java Programming 6 Autumn
    Computer Aided Verification 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    Advanced Computer Architectures 6 Spring

     

    Specialisation in Software Development

    Software plays a pivotal role in almost all aspects of our life, including transportation, communication, economy, and healthcare. We put trust in software to accomplish complex and vital tasks for us, such as managing our finances, sharing our family and friends’ memories, diagnosing diseases, flying aeroplanes or driving cars. The complexity of these tasks, while becoming transparent to us, does not go away: it is distilled into the software our civilization depends on. Indeed, we are already in the era of ultra-large-scale software systems, composed of millions of code components interacting among them.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Software Development” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    Software Analysis 6 Spring
    Software Architecture 6 Spring
    Software Quality & Testing 6 Spring

    Students graduating with this specialisation will have high employability in the industry.

     

    Specialisation in Theory and Algorithms

    Algorithms are at the core of every computing system. For that reason, the theory of computation and algorithms are fundamental to the training of computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

    Students graduating with a Master of Science in Informatics with strong training in Theory and Algorithms will be able to evaluate and solve complex problems not only in the field of their own expertise but also in interdisciplinary areas. Students develop strong analytical skills and foundational knowledge in computer science that can help them excel in any industrial or academic career setting in Informatics. Computer scientists with strong theoretical background are extremely flexible and thus in demand in nowadays high-tech ICT industry.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Theory and Algorithms” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Numerical Algorithms 6 Autumn
    Information & Physics 3 Spring
    Quantum Computing 6 Spring
  • Study plan 2021-2023

    The study programme consists of four semesters of full-time study (120 ECTS). Students select 30 ECTS of foundational courses (over the two years) and 60 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

    To broaden the student's perspective, in addition to courses from the other master's programmes of the Faculty, up to 6 ECTS of electives can be obtained by following any Master's course offered at USI.

    The students have the possibility to obtain a specialisation by writing the Master's thesis and taking at least 18 ECTS of courses in one of the following areas:

    • Artificial Intelligence
    • Computer Systems
    • Geometric and Visual Computing
    • Information Systems
    • Programming Languages
    • Software Development
    • Theory and Algorithms

     

    FOUNDATIONAL COURSES (30 ECTS out of 36 ECTS) ECTS Sem
    Algorithms & Complexity 6 Autumn
    Distributed Systems 6 Autumn
    High-Performance Computing 6 Autumn
    Information Security 6 Spring
    Machine Learning 6 Autumn
    Software Engineering 6 Autumn
         
    ELECTIVES (60 ECTS)    
    Advanced Java Programming 6 Autumn
    Computer Aided Verification 6 Autumn
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Numerical Algorithms 6 Autumn
    Software Performance 6 Autumn
    User Experience Design 6 Autumn
    Advanced Computer Architectures 6 Spring
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Geometric Algorithms 6 Spring
    Graph Deep Learning 3 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring
    Robotics 6 Spring
         
    Electives from other master programmes of the Faculty of Informatics    
    MSc in Artificial Intelligence    
    MSc in Computational Science    
    MSc in Financial Technology and Computing    
    MSc in Management & Informatics    
    MSc in Software & Data Engineering    
         
    MASTER THESIS (30 ECTS)    
    Master Thesis (can be started in the 3rd semester) 30 Spring

    Please be aware that slight changes in the study programme may occur.

    Specialisations

    • Artificial Intelligence

    A wide variety of techniques will be taught, including intelligent robotics, artificial deep neural networks, machine learning, metaheuristics optimization techniques, data mining, data analytics, simulation and distributed
    algorithms. The main courses are integrated with laboratory works where students have the possibility to use real robots and to practice with state of the art tools and methodologies.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Artificial Intelligence” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Advanced Topics in Machine Learning 3 Autumn
    Artificial Intelligence 6 Autumn
    Deep Learning Lab 6 Autumn
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Graph Deep Learning 3 Spring
    Robotics 6 Spring

    Students graduating with this specialisation will develop a taste for working on complex problems. In their future careers, they will be able to apply their knowledge in many interdisciplinary areas including robotics, business forecasting, intelligent search, video games, music and entertainment, chat bots, medical diagnostics, and self-driving cars, to name a few.

    • Computer Systems

    Think of the interconnected data management systems of a global institution: a bank, an airline, or a national government. Think about the large clusters of computers used by scientists to map the human genome. Think about a networked massively multiplayer game. Think of a telecommunication network such as the Internet or the 3G mobile network. Think about computers that help drive your car safely and efficiently. These are all distributed computer systems and, like them, many others are being developed and used pervasively in our modern society. Needless to say, computers and networks play a central role within these systems. They process, store, and transmit information to support a wide variety of tasks, ranging from the safety-critical operations of a transportation system to the business-critical functions of a bank, to the performance-critical computations of the scientific models studied by physicists or molecular biologists. The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a PhD.

    Course ECTS Sem
    Computer Aided Verification  6 Autumn
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Advanced Computer Architectures  6 Spring
    Advanced Networking 6 Spring

    The Computer Systems specialization of the Master of Science in Informatics prepares professionals capable of designing and developing modern distributed computer systems. In particular, the emphasis of the design taught is on dependability, which means that systems are engineered to withstand failures of system components and to gracefully sustain heavy workloads and/or intense communication traffic. The knowledge and technical expertise acquired in this specialization is an ideal basis for a career as a system engineer, with employment opportunities in virtually any company whose business depends on computing systems. Moreover, the analytical skills that characterize this specialization make up a versatile professional profile, as they are more generally applicable to a range of diverse problem-solving tasks.

    • Geometric and Visual Computing

    The last decade has witnessed a remarkable emergence and maturing of technologies dealing with visual and geometric data. Many methods that were in the domain of research labs have become classical and standard industry practice. Think of Google Goggles (a web service allowing the user to take a street image with a mobile phone and get information about the depicted objects), Google Street View and Microsoft Photosynth (photo tourism service, based on computer vision algorithms for building 3D models of cities from very large sets of images), Microsoft Kinect (an add-on to Xbox console allowing gesture-based control, based on computer vision technology to scan the 3D scene in real-time and pattern recognition algorithms to analyze the gestures), and the movie Avatar (setting a new standard both in computer graphics realism, but also remarkable for the use of very sophisticated 3D vision technologies during production). These examples belong to the field of Geometric and Visual Computing, dealing with processing and analyzing visual and geometric information. Geometric and Visual Computing is a combination of computer science (discrete algorithms, data structures, software engineering) and mathematical modelling (theoretical foundations and computational methods), which are used in the domains of computer graphics, computer vision, 2D and 3D signal processing, and pattern recognition. The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

    Course ECTS Sem
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Geometric Algorithms 6 Spring
    Graph Deep Learning 3 Spring
    Robotics 6 Spring

    Various aspects of geometric computing are required for jobs dealing with CAD/CAM systems, VLSI, geographic information systems, engineering, numerical simulations, special effects and graphics (e.g. movie industry), image processing and analysis, computer vision, and multidimensional data analysis. These jobs demand specialists combining a strong theoretical background in math, expertise in geometry, knowledge of computational methods, and software development skills.

    • Information Systems

    Students will learn how to design, develop and maintain large systems for the indexing and retrieval of all kind of information, from database records to textual information or multimedia and Web hypermedia (images, video, etc). An ICT professional requires nowadays a mix of technical know-how comprising skills such as project management, information architecture, and human-computer interaction. This specialisation is designed to address these gaps and to educate ICT professionals to play a leading role.

    Course ECTS Sem
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    User Experience Design 6 Autumn
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Data Analytics 6 Spring

    The Information Systems specialisation aims at preparing students for leadership careers in the area of information systems design and development, information systems quality assurance, information systems integration and information systems project management.

    • Programming Languages

    Programming languages are a medium for communicating our intentions to the computer and to each other. The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis. Programming languages is an active area. There is a great need for new programming abstractions to be developed, new languages invented, and existing languages extended to be able to effectively program and take full advantage of new platforms and architectures.

    Course ECTS Sem
    Advanced Java Programming 6 Autumn
    Computer Aided Verification 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    Advanced Computer Architectures 6 Spring

    Graduates will be prepared to work in fields related to program understanding, analysis, manipulation, and transformation. They will acquire the tools and techniques needed to specify and implement language-based solutions. Students will study fundamental aspects of programming languages, both from the theoretical and the practical side, preparing them to become industry professionals or to continue on towards a PhD.

    • Software Development

    Software plays a pivotal role in almost all aspects of our life, including transportation, communication, economy, and healthcare. We put trust in software to accomplish complex and vital tasks for us, such as managing our finances, sharing our family and friends’ memories, diagnosing diseases, flying aeroplanes or driving cars. The complexity of these tasks, while becoming transparent to us, does not go away: it is distilled into the software our civilization depends on. Indeed, we are already in the era of ultra-large-scale software systems, composed of millions of code components interacting among them.

    Across the two years students must acquire:

    • 30 ECTS out of 36 ECTS of core courses
    • 18 ECTS of “Software Development” tagged courses and write their thesis in the same area

    6 ECTS can be acquired from non-INF Master programmes at USI.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Programming Styles 3 Autumn
    Software Design & Modeling 6 Autumn
    Software Performance 6 Autumn
    Software Analysis 6 Spring
    Software Architecture 6 Spring
    Software Quality & Testing 6 Spring

    Students graduating with this specialisation will have high employability in the industry.

    • Theory and Algorithms

    Algorithms are at the core of every computing system. For that reason, the theory of computation and algorithms are fundamental to the training of computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Numerical Algorithms 6 Autumn
    Geometric Algorithms 6 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring

    Students graduating with a Master of Science in Informatics with strong training in Theory and Algorithms will be able to evaluate and solve complex problems not only in the field of their own expertise but also in interdisciplinary areas. Students develop strong analytical skills and foundational knowledge in computer science that can help them excel in any industrial or academic career setting in Informatics. Computer scientists with strong theoretical background are extremely flexible and thus in demand in nowadays high-tech ICT industry.

  • Study plan 2020-2022

    The study programme consists of four semesters full-time study (120 ECTS). Students select 30 ECTS of foundational courses (over the two years) and 60 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

    To broaden the student's perspective, in addition to courses from the other master programmes of the Faculty, up to 6 ECTS of electives can be obtained by following any Master course offered at USI.

    The students have the possibility to obtain a specialisation by writing the Master's thesis and taking at least 18 ECTS of courses in one of the following areas:

    • Artificial Intelligence (from A.Y. 2021/22)
    • Computer Systems
    • Geometric and Visual Computing
    • Information Systems
    • Programming Languages
    • Software Development (from A.Y. 2021/22)
    • Theory and Algorithms
    FOUNDATIONAL COURSES (30 ECTS out of 36 ECTS) ECTS Sem
    Algorithms & Complexity 6 Autumn
    Distributed Systems 6 Autumn
    High-Performance Computing 6 Autumn
    Information Security 6 Spring
    Machine Learning 6 Autumn
    Software Engineering 6 Autumn
         
    ELECTIVES (60 ECTS)    
    Advanced Java Programming 6 Autumn
    Computer Aided Verification 6 Autumn
    Distributed Algorithms I 3 Autumn
    Distributed Algorithms II - Protocols and Techniques for Blockchains 3 Autumn
    Mobile and Wearable Computing 6 Autumn
    Numerical Algorithms 6 Autumn
    Software Performance 6 Autumn
    User Experience Design 6 Autumn
    Advanced Computer Architectures 6 Spring
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Geometric Algorithms 6 Spring
    Graph Deep Learning 3 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring
    Robotics 6 Spring
         
    Electives from other master programmes of the Faculty of Informatics    
    MSc in Artificial Intelligence    
    MSc in Computational Science    
    MSc in Financial Technology and Computing    
    MSc in Management & Informatics    
    MSc in Software & Data Engineering    
         
    MASTER THESIS (30 ECTS)    
    Master Thesis (can be started in the 3rd semester) 30 Spring

    Please be aware that slight changes in the study programme may occur.

     

    Specialisations

    • Computer Systems

    Think of the interconnected data management systems of a global institution: a bank, an airline, or a national government. Think about the large clusters of computers used by scientists to map the human genome. Think about a networked massively multiplayer game. Think of a telecommunication network such as the Internet or the 3G mobile network. Think about computers that help drive your car safely and efficiently. These are all distributed computer systems and, like them, many others are being developed and used pervasively in our modern society. Needless to say, computers and networks play a central role within these systems. They process, store, and transmit information to support a wide variety of tasks, ranging from the safety-critical operations of a transportation system to the business-critical functions of a bank, to the performance-critical computations of the scientific models studied by physicists or molecular biologists. The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a PhD.

    Course ECTS Sem
    Computer Aided Verification  6 Autumn
    Distributed Algorithms I 3 Autumn
    Distributed Algorithms II - Protocols and Techniques for Blockchains 3 Autumn
    Mobile and Wearable Computing 6 Autumn
    Advanced Computer Architectures  6 Spring
    Advanced Networking 6 Spring

    The Computer Systems specialization of the Master of Science in Informatics prepares professionals capable of designing and developing modern distributed computer systems. In particular, the emphasis of the design taught is on dependability, which means that systems are engineered to withstand failures of system components and to gracefully sustain heavy workloads and/or intense communication traffic. The knowledge and technical expertise acquired in this specialization is an ideal basis for a career as a system engineer, with employment opportunities in virtually any company whose business depends on computing systems. Moreover, the analytical skills that characterize this specialization make up a versatile professional profile, as they are more generally applicable to a range of diverse problem-solving tasks.

    • Geometric and visual computing

    The last decade has witnessed a remarkable emergence and maturing of technologies dealing with visual and geometric data. Many methods that were in the domain of research labs have become classical and standard industry practice. Think of Google Goggles (a web service allowing the user to take a street image with a mobile phone and get information about the depicted objects), Google Street View and Microsoft Photosynth (photo tourism service, based on computer vision algorithms for building 3D models of cities from very large sets of images), Microsoft Kinect (an add-on to Xbox console allowing gesture-based control, based on computer vision technology to scan the 3D scene in real-time and pattern recognition algorithms to analyze the gestures), and the movie Avatar (setting a new standard both in computer graphics realism, but also remarkable for the use of very sophisticated 3D vision technologies during production). These examples belong to the field of Geometric and Visual Computing, dealing with processing and analyzing visual and geometric information. Geometric and Visual Computing is a combination of computer science (discrete algorithms, data structures, software engineering) and mathematical modelling (theoretical foundations and computational methods), which are used in the domains of computer graphics, computer vision, 2D and 3D signal processing, and pattern recognition. The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

    Course ECTS Sem
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Geometric Algorithms 6 Spring
    Graph Deep Learning 3 Spring
    Robotics 6 Spring

    Various aspects of geometric computing are required for jobs dealing with CAD/CAM systems, VLSI, geographic information systems, engineering, numerical simulations, special effects and graphics (e.g. movie industry), image processing and analysis, computer vision, and multidimensional data analysis. These jobs demand specialists combining a strong theoretical background in math, expertise in geometry, knowledge of computational methods, and software development skills.

    • Information Systems

    Students will learn how to design, develop and maintain large systems for the indexing and retrieval of all kind of information, from database records to textual information or multimedia and Web hypermedia (images, video, etc). An ICT professional requires nowadays a mix of technical know-how comprising skills such as project management, information architecture, and human-computer interaction. This specialisation is designed to address these gaps and to educate ICT professionals to play a leading role.

    Course ECTS Sem
    Distributed Algorithms I 3 Autumn
    Distributed Algorithms II - Protocols and Techniques for Blockchain 3 Autumn
    Mobile and Wearable Computing 6 Autumn
    User Experience Design 6 Autumn
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Data Analytics 6 Spring

    The Information Systems specialisation aims at preparing students for leadership careers in the area of information systems design and development, information systems quality assurance, information systems integration and information systems project management.

    • Programming Languages

    Programming languages are a medium for communicating our intentions to the computer and to each other. The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis. Programming languages is an active area. There is a great need for new programming abstractions to be developed, new languages invented, and existing languages extended to be able to effectively program and take full advantage of new platforms and architectures.

    Course ECTS Sem
    Advanced Java Programming 6 Autumn
    Computer Aided Verification 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    Advanced Computer Architectures 6 Spring

    Graduates will be prepared to work in fields related to program understanding, analysis, manipulation, and transformation. They will acquire the tools and techniques needed to specify and implement language-based solutions. Students will study fundamental aspects of programming languages, both from the theoretical and the practical side, preparing them to become industry professionals or to continue on towards a PhD.

    • Theory and Algorithms

    Algorithms are at the core of every computing system. For that reason, the theory of computation and algorithms are fundamental to the training of computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Numerical Algorithms 6 Autumn
    Geometric Algorithms 6 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring

    Students graduating with a Master of Science in Informatics with strong training in Theory and Algorithms will be able to evaluate and solve complex problems not only in the field of their own expertise but also in interdisciplinary areas. Students develop strong analytical skills and foundational knowledge in computer science that can help them excel in any industrial or academic career setting in Informatics. Computer scientists with strong theoretical backgrounds are extremely flexible and thus in demand in nowadays high-tech ICT industry.

  • Study plan 2019-2021

    Study plan of the Master in Informatics - curriculum 2019-2021

    The study programme consists of four semesters full-time study (120 ECTS). Students select 30 ECTS of foundational courses (over the two years) and 60 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

    To broaden the student's perspective, in addition to courses from the other master programmes of the Faculty, up to 6 ECTS of electives can be obtained by following any Master course offered at USI.

    The students have the possibility to obtain a specialisation by writing the Master's thesis and taking at least 18 ECTS of courses in one of the following areas:

    • Computer Systems
    • Geometric and Visual Computing
    • Information Systems
    • Programming Languages
    • Theory and Algorithms

     

    FOUNDATIONAL COURSES (30 ECTS out of 36 ECTS) ECTS Sem
    Algorithms & Complexity 6 Autumn
    Distributed Systems 6 Autumn
    High-Performance Computing 6 Autumn
    Information Security 6 Spring
    Machine Learning 6 Autumn
    Software Engineering 6 Autumn
         
    ELECTIVES (60 ECTS)    
    Advanced Java Programming 3 Autumn
    Computer Aided Verification 6 Autumn
    Distributed Algorithms* 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Numerical Algorithms 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    User Experience Design 6 Autumn
    Advanced Computer Architectures 6 Spring
    Advanced Networking 6 Spring
    Business Process Modeling, Management and Mining 3 Spring
    Compiler Construction 6 Spring
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Data Analytics 6 Spring
    Geometric Algorithms 6 Spring
    Geometric Deep Learning 3 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring
    Robotics 6 Spring
         
    Electives from other master programmes of the Faculty of Informatics    
    MSc in Artificial Intelligence    
    MSc in Computational Science    
    MSc in Financial Technology and Computing    
    MSc in Management & Informatics    
    MSc in Software & Data Engineering (selected courses)    
         
    MASTER THESIS (30 ECTS)    
    Master Thesis (can be started in the 3rd semester) 30 Spring

    * The course is not offered in the Academic Year 2019/20.

     

    Specialisation

    • Computer Systems

    Think of the interconnected data management systems of a global institution: a bank, an airline, or a national government. Think about the large clusters of computers used by scientists to map the human genome. Think about a networked massively multiplayer game. Think of a telecommunication network such as the Internet or the 3G mobile network. Think about the computers that help drive your car safely and efficiently. These are all distributed computer systems and, like them, many others are being developed and used pervasively in our modern society. Needless to say, computers and networks play a central role within these systems. They process, store, and transmit information to support a wide variety of tasks, ranging from the safety-critical operations of a transportation system, to the business critical functions of a bank, to the performance-critical computations of the scientific models studied by physicists or molecular biologists. The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a Ph.D.

    Course ECTS Sem
    Computer Aided Verification  6 Autumn
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    Advanced Computer Architectures  6 Spring
    Advanced Networking 6 Spring

    The Computer Systems specialization of the Master of Science in Informatics prepares professionals capable of designing and developing modern distributed computer systems. In particular, the emphasis of the design taught is on dependability, which means that systems are engineered to withstand failures of system components and to gracefully sustain heavy workloads and/or intense communication traffic. The knowledge and technical expertise acquired in this specialization is an ideal basis for a career as a system engineer, with employment opportunities in virtually any company whose business depends on computing systems. Moreover, the analytical skills that characterize this specialization make up a versatile professional profile, as they are more generally applicable to a range of diverse problem-solving tasks.

     

    • Geometric and Visual Computing

    The last decade has witnessed a remarkable emergence and maturing of technologies dealing with visual and geometric data. Many methods that were in the domain of research labs have become classical and standard industrial practice. Think of Google Goggles (a web service allowing the user to take a street image with a mobile phone and get information about the depicted objects), Google Street View and Microsoft Photosynth (photo tourism service, based on computer vision algorithms for building 3D models of cities from very large sets of images), Microsoft Kinect (an add-on to Xbox console allowing gesture-based control, based on computer vision technology to scan the 3D scene in real-time and pattern recognition algorithms to analyze the gestures), and the movie Avatar (setting a new standard both in computer graphics realism, but also remarkable for the use of very sophisticated 3D vision technologies during production). These examples belong to the field of Geometric and Visual Computing, dealing with processing and analyzing visual and geometric information. Geometric and Visual Computing is a combination of computer science (discrete algorithms, data structures, software engineering) and mathematical modeling (theoretical foundations and computational methods), which are used in the domains of computer graphics, computer vision, 2D and 3D signal processing, and pattern recognition. The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

    Course ECTS Sem
    Computational Fabrication 6 Spring
    Computer Vision & Pattern Recognition 6 Spring
    Geometric Algorithms 6 Spring
    Geometric Deep Learning 3 Spring
    Robotics 6 Spring

    Various aspects of geometric computing are required for jobs dealing with CAD/CAM systems, VLSI, geographic information systems, engineering, numerical simulations, special effects and graphics (e.g. movie industry), image processing and analysis, computer vision, and multidimensional data analysis. These jobs demand specialists combining strong theoretical background in math, expertise in geometry, knowledge of computational methods, and software development skills.

     

    • Information Systems

    Students will learn how to design, develop and maintain large systems for the indexing and retrieval of all kind of information, from database records to textual information or multimedia and Web hypermedia (images, video, etc). An ICT professional requires nowadays a mix of technical know-how comprising skills such as project management, information architecture, and human-computer interaction. This specialisation is designed to address these gaps and to educate ICT professionals to play a leading role.

    Course ECTS Sem
    Distributed Algorithms 6 Autumn
    Mobile and Wearable Computing 6 Autumn
    User Experience Design 6 Autumn
    Business Process Modeling, Management and Mining 3 Spring
    Compiler Construction 6 Spring
    Data Analytics 6 Spring

    The Information Systems specialisation aims at preparing students for leadership careers in the area of information systems design and development, information systems quality assurance, information systems integration and information systems project management.

     

    • Programming Languages

    Programming languages are a medium for communicating our intentions to the computer and to each other. The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis. Programming languages is an active area. There is a great need for new programming abstractions to be developed, new languages invented, and existing languages extended to be able to effectively program and take full advantage of new platforms and architectures.

    Course ECTS Sem
    Advanced Java Programming 3 Autumn
    Computer Aided Verification 6 Autumn
    Programming Styles 3 Autumn
    Software Performance 6 Autumn
    Advanced Computer Architectures 6 Spring
    Compiler Construction 6 Spring

    Graduates will be prepared to work in fields related to program understanding, analysis, manipulation, and transformation. They will acquire tools and techniques needed to specify and implement language-based solutions. Students will study fundamental aspects of programming languages, both from the theoretical and the practical side, preparing them to become industry professionals or to continue on towards a Ph.D.

     

    • Theory and Algorithms

    Algorithms are at the core of every computing system. For that reason, the theory of computation and algorithms are fundamental to the training of computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

    Course ECTS Sem
    Computer Aided Verification 6 Autumn
    Numerical Algorithms 6 Autumn
    Geometric Algorithms 6 Spring
    Information & Physics 3 Spring
    Quantum Computing 6 Spring

    Students graduating with a Master of Science in Informatics with strong training in Theory and Algorithms will be able to evaluate and solve complex problems not only in the field of their own expertise but also in interdisciplinary areas. Students develop strong analytical skills and foundational knowledge in computer science that can help them excel in any industrial or academic career setting in Informatics. Computer scientists with strong theoretical background are extremely flexible and thus in demand in nowadays high-tech ICT industry.

      Please be aware that slight changes in the study programme may occur.

    • Study plan 2018-2020

      Study plan of the Master in Informatics - curriculum 2018-2020

       

      The study programme consists of four semesters full-time study (120 ECTS). Students select 24 ECTS of foundational courses (over the two years) and 66 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

      To broaden the student's perspective, in addition to courses from the other master programmes of the Faculty, up to 6 ECTS of electives can be obtained by following any Master course offered at USI. 

      specialisation can be obtained by writing the Master's thesis and taking 18 ECTS of courses in one of the following research areas:

      • Computer Systems
      • Geometric and Visual Computing
      • Information Systems
      • Programming Languages
      • Theory and Algorithms

       

      FOUNDATIONAL COURSES (24 ECTS) ECTS Sem
      Algorithms & Complexity 6 Fall
      Distributed Systems 6 Fall
      High Performance Computing 6 Fall
      Information Security 6 Spring
      Machine Learning 6 Fall
           
      ELECTIVES (66 ECTS)    
      Advanced Java Programming 6 Fall
      Distributed Algorithms 6 Fall
      Mobile and Wearable Computing 6 Fall
      Numerical Algorithms 6 Fall
      Software Engineering 6 Fall
      Software Performance 6 Fall
      User Experience Design 6 Fall
      Advanced Computer Architectures 6 Spring
      Advanced Networking 6 Spring
      Business Process Modeling, Management and Mining 3 Spring
      Compiler Construction 6 Spring
      Computational Fabrication 6 Spring
      Computer Aided Verification 6 Spring
      Computer Vision & Pattern Recognition 6 Spring
      Data Analytics 6 Spring
      Geometric Algorithms 6 Spring
      Geometric Deep Learning 3 Spring
      Quantum Computing 6 Spring
      Robotics 6 Spring
           
      Electives from other master programmes of the Faculty of Informatics    
      MSc in Artificial Intelligence    
      MSc in Computational Science    
      MSc in Software & Data Engineering (selected courses)    
      MSc in Management & Informatics    
      MSc in Financial Technology and Computing    
           
      MASTER THESIS (30 ECTS)    
      Master Thesis (can be started in the 3rd semester) 30 Spring

       

      Specialisation

      • Computer Systems

      The Computer Systems specialization of the Master of Science in Informatics prepares professionals capable of designing and developing modern distributed computer systems. In particular, the emphasis of the design taught is on dependability, which means that systems are engineered to withstand failures of system components and to gracefully sustain heavy workloads and/or intense communication traffic. The knowledge and technical expertise acquired in this specialization is an ideal basis for a career as a system engineer, with employment opportunities in virtually any company whose business depends on computing systems. Moreover, the analytical skills that characterize this specialization make up a versatile professional profile, as they are more generally applicable to a range of diverse problem-solving tasks.

      Course ECTS Sem
      Distributed Algorithms 6 Fall
      Mobile and Wearable Computing 6 Fall
      Advanced Computer Architectures  6 Spring
      Advanced Networking 6 Spring
      Computer Aided Verification  6 Spring

       

      • Geometric and Visual Computing

      The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

      Course ECTS Sem
      Computational Fabrication 6 Spring
      Computer Vision & Pattern Recognition 6 Spring
      Geometric Algorithms 6 Spring
      Geometric Deep Learning 3 Spring
      Robotics 6 Spring

       

      • Information Systems

      Students will learn how to design, develop and maintain large systems for the indexing and retrieval of all kind of information, from database records to textual information or multimedia and Web hypermedia (images, video, etc).

      Course ECTS Sem
      Distributed Algorithms 6 Fall
      Mobile and Wearable Computing 6 Fall
      User Experience Design 6 Fall
      Business Process Modeling, Management and Mining 3 Spring
      Compiler Construction 6 Spring
      Data Analytics 6 Spring

       

      • Programming Languages

      The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis.

      Course ECTS Sem
      Advanced Java Programming 6 Fall
      Software Performance 6 Fall
      Advanced Computer Architectures 6 Spring
      Compiler Construction 6 Spring
      Computer Aided Verification 6 Spring

       

      • Theory and Algorithms

      Algorithms are at the core of every computing system. For that reason, the theory of computation and algorithms are fundamental to the training of computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

      Course ECTS Sem
      Numerical Algorithms 6 Fall
      Computer Aided Verification 6 Spring
      Geometric Algorithms 6 Spring
      Quantum Computing 6 Spring

       

      Changes in the study plan may occurr. In case of discrepancies, or for any legal purpose, the study plan indicated by the Director of the Master or the Dean's office of the Faculty of Informatics shall prevail.

       

       

    • Study plan 2017-2019

      Study plan of the Master in Informatics - curriculum 2017-2019

       

      FOUNDATIONAL COURSES (24 ECTS)                      ECTS Sem
      Advanced Programming & Design* 6 Fall
      Algorithms & Complexity 6 Fall
      Distributed Systems 6 Fall
      High Performance Computing 6 Fall
      Information Security 6 Spring
      Machine Learning 6 Fall

       

      ELECTIVES (66 ECTS) ECTS Sem
      Distributed Algorithms 6 Fall
      Mobile Computing 6 Fall
      Numerical Algorithms 3 Fall
      Software Engineering 6 Fall
      Software Performance 6 Fall
      User Experience Design 6 Fall
      Advanced Networking* 6 Spring
      Advanced Computer Architectures 6 Spring
      Business Process Modeling, Management and Mining 3 Spring
      Compiler Construction 6 Spring
      Computer Aided Verification* 6 Spring
      Computer Vision & Pattern Recognition* 6 Spring
      Data Analytics 6 Spring
      Geometric Algorithms 6 Spring
      Geometric Deep Learning* 3 Spring
      Geometry Processing* 6 Spring
      Information & Physics 3 Spring
      Physical Computing 6 Spring
      Quantum Computing 6 Spring
      Robotics 6 Spring
       

      Electives from other master programmes of the Faculty of Informatics

      MSc in Artificial Intelligence
      MSc in Computational Science
      MSc in Cyber-Physical and Embedded Systems
      MSc in Software & Data Engineering (selected courses)
      MSc in Management & Informatics
      MSc in Financial Technology and Computing

       

      MASTER THESIS (30 ECTS) ECTS      Sem
      Master Thesis (can be started in the 3rd semester) 30 Spring

      * please note that these courses will not be offered in the academic year 2017/18

       

      Specialisation

      • Computer Systems

      The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a Ph.D.

      List of courses ECTS and semester
      Advanced Networking 6 ECTS – Fall 
      Distributed Algorithms 6 ECTS – Fall 
      Mobile Computing 6 ECTS – Fall 
      Advanced Computer Architectures 6 ECTS – Spring 
      Computer Aided Verification  6 ECTS – Spring 
      Physical Computing 6 ECTS – Spring

       

      • Geometric and Visual Computing

      The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

      List of courses ECTS and semester
      Computer Vision & Pattern Recognition 6 ECTS – Spring
      Geometric Algorithms 6 ECTS – Spring
      Geometric Deep Learning 3 ECTS – Spring
      Geometry Processing 6 ECTS – Spring
      Robotics 6 ECTS – Spring

       

      • Information Systems

      Students will learn how to design, develop and maintain large systems forthe indexing and retrieval of all kind of information, from database records totextual information or multimedia and Web hypermedia (images, video, etc).

      List of courses ECTS and semester
      Distributed Algorithms 6 ECTS – Fall
      Mobile Computing 6 ECTS – Fall
      User Experience Design 6 ECTS – Fall
      Business Process Modeling, Management and Mining 3 ECTS – Spring
      Compilers 6 ECTS – Spring
      Data Analytics 6 ECTS – Spring
      Physical Computing 6 ECTS – Spring

       

      • Programming Languages

      The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis.

      List of courses ECTS and semester
      Software Performance 6 ECTS – Fall
      Advanced Computer Architectures 6 ECTS – Spring
      Compiler Construction 6 ECTS – Spring
      Computer Aided Verification 6 ECTS – Spring

       

      • Theory and Algorithms

      Algorithms are at the core of every computing system. For that reason, theory of computation and algorithms are fundamental to the training of the computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

      List of courses ECTS and semester
      Numerical Algorithms 3 ECTS – Fall
      Computer Aided Verification 6 ECTS – Spring
      Geometric Algorithms 6 ECTS – Spring
      Information & Physics 3 ECTS – Spring
      Quantum Computing 6 ECTS – Spring

       

      Changes in the study plan may occurr. In case of discrepancies, or for any legal purpose, the study plan indicated by the Director of the Master or the Dean's office of the Faculty of Informatics shall prevail.

    • Study plan 2016-2018

      Study plan of the Master in Informatics - curriculum 2016-2018

       

      The study plan consists of four semesters full-time study (120 ECTS).

      Students select 24 ECTS of foundational courses (over the two years) and 66 ECTS of electives based on their interests, plus a substantial Master's thesis (30 ECTS).

      A specialisation can be obtained by writing the Master's thesis and taking 18 ECTS of courses in one of the following research areas:

      • Computer Systems
      • Geometric and Visual Computing
      • Information Systems
      • Programming Languages
      • Theory and Algorithms

       

      Study plan

      Course ECTS and semester
         
      Foundational Courses (24 ETCS)  
      Advanced Programming & Design 6 ECTS – Fall
      Algorithms & Complexity 6 ECTS – Fall
      Distributed Systems 6 ECTS – Fall
      High Performance Computing 6 ECTS – Fall
      Information Security 6 ECTS – Spring
      Machine Learning 6 ECTS – Fall
         
      Electives (66 ETCS)  
      Advanced Networking 6 ECTS – Fall
      Distributed Algorithms 6 ECTS – Fall
      Mobile Computing 6 ECTS – Fall
      Numerical Algorithms 3 ECTS – Fall
      Software Performance  6 ECTS – Fall
      User Experience Design 6 ECTS – Fall
      Advanced Computer Architectures 6 ECTS – Spring
      Business Process Modeling, Management and Mining 3 ECTS – Spring
      Compilers 6 ECTS – Spring
      Computer Aided Verification** 6 ECTS – Spring
      Computer Vision & Pattern Recognition** 6 ECTS – Spring
      Data Analytics 6 ECTS – Spring
      Geometric Algorithms 6 ECTS – Spring
      Geometric Deep Learning** 3 ECTS – Spring
      Geometry Processing** 6 ECTS – Spring
      Information & Physics 3 ECTS – Spring
      Physical Computing 6 ECTS – Spring
      Quantum Computing 6 ECTS – Spring
      Robotics 6 ECTS – Spring
         
      Master Thesis (30 ETCS)  
      Master Thesis (can be started in the 3rd semester) 30 ECTS – Spring

       

      Specialisation

      • Computer Systems

      The specialization in Computer Systems provides students with an in-depth perspective on advanced topics of dynamic, dependable, distributed computer systems. The specialization focuses on the design, implementation, and performance analysis of reliable, secure, and scalable computer systems. It combines the study of fundamental aspects of distributed systems with a hands-on approach, preparing professionals both for working in the industry and continuing towards a Ph.D.

      List of courses ECTS and semester
      Advanced Networking 6 ECTS – Fall 
      Distributed Algorithms 6 ECTS – Fall 
      Mobile Computing 6 ECTS – Fall 
      Advanced Computer Architectures 6 ECTS – Spring 
      Computer Aided Verification**  6 ECTS – Spring 
      Physical Computing 6 ECTS – Spring

       

      • Geometric and Visual Computing

      The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.

      List of courses ECTS and semester
      Computer Vision & Pattern Recognition 6 ECTS – Spring
      Geometric Algorithms 6 ECTS – Spring
      Geometric Deep Learning 3 ECTS – Spring
      Geometry Processing 6 ECTS – Spring
      Robotics 6 ECTS – Spring

       

      • Information Systems

      Students will learn how to design, develop and maintain large systems forthe indexing and retrieval of all kind of information, from database records totextual information or multimedia and Web hypermedia (images, video, etc).

      List of courses ECTS and semester
      Distributed Algorithms 6 ECTS – Fall
      Mobile Computing 6 ECTS – Fall
      User Experience Design 6 ECTS – Fall
      Business Process Modeling, Management and Mining 3 ECTS – Spring
      Compilers 6 ECTS – Spring
      Data Analytics 6 ECTS – Spring
      Physical Computing 6 ECTS – Spring

       

      • Programming Languages

      The field of programming languages studies organizing principles that link other areas cutting across all of computer science. The field covers programming language design, compilers, runtime systems, type systems, program verification, performance, and static and dynamic analysis.

      List of courses ECTS and semester
      Software Performance 6 ECTS – Fall
      Advanced Computer Architectures 6 ECTS – Spring
      Compilers 6 ECTS – Spring
      Computer Aided Verification 6 ECTS – Spring

       

      • Theory and Algorithms

      Algorithms are at the core of every computing system. For that reason, theory of computation and algorithms are fundamental to the training of the computer engineers and scientists. A computer specialist strong in theory can tackle important problems in virtually any field of the computer industry. The performance of any software system depends on the efficiency of its algorithms and data structures. Think computational problems that arise in a bank, in an airline, in microelectronics, in telecommunications, in biology. There are complex algorithms hiding behind any software tool that can successfully address such problems.

      List of courses ECTS and semester
      Numerical Algorithms 3 ECTS – Fall
      Computer Aided Verification 6 ECTS – Spring
      Geometric Algorithms 6 ECTS – Spring
      Information & Physics 3 ECTS – Spring
      Quantum Computing 6 ECTS – Spring

       

      Changes in the study plan may occurr. In case of discrepancies, or for any legal purpose, the study plan indicated by the Director of the Master or the Dean's office of the Faculty of Informatics shall prevail.

    Facoltà

    Pubblico

    Tema

    Aggiornato al: 17 gennaio 2024