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 2024-2026
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 6 6
Electives
6
Third Semester
ECTS Core Courses
6 6 Master Thesis
9 Electives
9 Fourth semester
ECTS Core Courses
3 21 Electives
6 Electives Autumn Semester
6 6 6
6 6
3
6 6 3 6 3 Electives Spring Semester
6 6 6 6 3 6 6
6 3 6 Introduction to Partial Differential Equations
6 4 6 6
6 Changes in the study programme may occur.
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Research summer internships for students - UROP Internships
The Faculty of Informatics encourages and promotes the talent of its Bachelor and Master students by offering them summer internships in academic research within the programme Undergraduate Research Opportunities Program - UROP.
Internships are extracurricular, and access is on a competitive basis. Students work one-on-one with an advisor to develop a deeper understanding of both the concepts taught during the semester and the research topic. Students considering continuing in academia should seriously consider applying for a UROP position.
All research opportunities for this year are listed here.
See all the job and internship opportunities in the USI Job Bank.
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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
Admission to the A.Y. 2024/25
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:
Score IELTS 6.5 TOEFL Internet-based: 85 Cambridge English First grade B TOEIC Listening & Reading: 860
Speaking: 170
Writing: 170Important:
- The language certificate must be included in the application package: candidates whose Bachelor's was entirely taught in English must upload an official document mentioning the tuition language (e.g., official transcript, diploma supplement, or any other official certificate issued by the university) in the application form.
- We only accept the above English qualifications (IELTS, TOEFL, Cambridge English, TOEIC).
- The certificate must still be valid at the point of the application. We generally cannot accept language test results older than three years as of September 1st.
- Certificates obtained by passing the IELTS Academic Online or TOEFL iBT Home Edition tests may also be submitted for admission to the programme.
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.
