Structure and contents
Artificial Intelligence may not only be the most exciting field in computer science, but of science in general. In fact, the best scientists of the future might even be AIs themselves. Hardware soon will have more raw computational power (CP) than human brains, since CP per cent is still growing by a factor of 100-1000 per decade. And there is no reason to believe that general problem solving software similar to that of humans will be lacking: there already exist mathematically optimal (though not yet practical) universal problem solvers developed at IDSIA. And existing highly practical (but not quite as universal) AI already learn from experience, outperforming humans in more and more fields. For example, biologically plausible deep / recurrent artificial neural networks are learning to solve pattern recognition tasks that seemed infeasible only 10 years ago. Examples: images, handwriting, traffic signs, since 2011 even with superhuman performance - no end in sight. Even creativity has been formalized such that it can now be implemented on machines. The current developments in AI may soon lead to the end of history as we know it (more), and as an IS master student you can become part of this revolution.
Artificial Intelligence systems have knowledge, beliefs, preferences and goals, and they have informational as well as motivational attitudes. They observe, learn, communicate, plan, anticipate and commit. They are able to reason about other systems and their own internal states, to simulate and optimize their performance. AI systems react to dynamic situations adapting their capabilities through learning mechanisms, with a high degree of autonomy.
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Study programme 2021-2023
In this master programme a wide variety of techniques will be taught, including intelligent robotics, artificial deep neural networks, machine learning, meta-heuristics 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. After the first few lectures of the basic Machine Learning course, AI master students will already know how to train self-learning artificial neural networks to recognize the images and handwritings to the right better than any other known method.
First Semester
ECTS Core Courses
6 3 6 3 Elective courses
12 Second Semester
ECTS Core Courses
6 6 Electives
18 Third Semester
ECTS Core Courses
6 6 9 Electives
9 Fourth semester
ECTS Core Courses
3 Data Analytics*
6 21 Electives Autumn Semester
3 6 6 3 6 6 3 6 3 Electives Spring Semester
6 6 6 6 6 3 3 6 6 6 *only for 2021/22 students (originally 1st-year course)
Changes in the study programme may occur.
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Teaching
Our Artificial Intelligence program boasts highly motivated teachers, who are dedicated and very active researchers both from the Faculty of Informatics and IDSIA.
They are all actively involved in EU, FNS, CTI and industry projects. Their research activities cover subjects such as deep learning in neural networks, intelligent and collective robotics, data mining, nature-inspired optimization, simulation, approximation algorithms and intelligent information retrieval. The coursework material, software tools and robots reflects the latest state of the art. Further opportunities will arise through the thesis which may open the path towards PhD studies.
Academic Director: Luca Maria Gambardella
Co-Director: Jürgen Schmidhuber
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Language
The admission to English-language Master programmes at USI requires a good command of English. Non-native English speakers applying to the Master’s or whose previous degree was obtained in another language, are required to provide an internationally acknowledged language certificate equal to the B2 level as defined by the Common European Framework of Reference for language learning (CEFR) or equivalent (e.g. TOEFL, IELTS, etc.).
The B2 level on the CEFR corresponds to the following scores in internationally acknowledged exams:
IELTS*
5.5
TOEFL*
Computer-based: 183
Internet-based*: 65
Paper-based: 513Cambridge English
B2 First
TOEIC
Listening & Reading: 785
Speaking: 150
Writing: 160Students admitted under the above-mentioned condition must achieve a C1 competence in English within the maximum time required to obtain the Master's degree.
The level can be certified either by attending a language course offered at USI during the Fall and Spring semester, and by taking the final exam, or by providing an internationally acknowledged language certificate*.* The C1 level on the CEFR corresponds to the following scores in internationally acknowledged exams:
IELTS
7.0
TOEFL
Internet-based: 100
Cambridge English
C1 Advanced, grade C or above
BEC (Business English), grade C or aboveTOEIC
Listening & Reading: 945
Speaking: 180
Writing: 180We only accept the English qualifications mentioned above. The certificate must still be valid at the point of the application. In general, we are not able to accept language test results older than 3 years, as of September 1st.
Italian
As Lugano is located in the Italian-speaking part of Switzerland, students might be interested in acquiring the basics in Italian.
The Università della Svizzera italiana offers a free of charge Italian language course: further information can be found here.Academic Year 2021/22
When do I have to submit my English language certification?
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Faculty of Communication, Culture and Society / Economics / Informatics
The language certification should be included in the application package. Exceptions will be made for those who can prove cancellation of international certificates exam sessions.
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