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Data Science Courses

For more information about the courses offered for the PhD programme in Data Science (DS), please visit the webpage of the programme. The formal learning opportunities will be flanked with a vigorous programme of online seminars (the “SISSA Data Science Seminar Series”, or SISSA DS 3 ), held approximately fortnightly from January 2021, with a focus on showcasing a young and diverse line-up of world-class speakers from all over the world. Further details will be published on this webpage.

Students from other PhD programmes who are interested in following our modules are requested to register their interest by filling out this form. This is for logistical (especially in view of COVID-19 restrictions to teaching spaces) and pedagogical reasons. Deadline is Fri Oct 2nd 2020.

Please, notice that MAMA PhD students can plan 33% of their credits (i.e. 50 hrs) from the courses listed below.

Courses of the Academic Year 2020-2021

Lecturer Title Duration Period CFU
Andrea De Simone Introduction to Statistical Modelling and Inference 26 h October
Guido Sanguinetti Bayesian inference I 36 h October - December 6
Jean Barbier Information Theory and Inference 26 h November - December
Roberto Trotta Bayesian Inference II 36 h January - February 6
Alessandro Laio, Alex Rodriguez Unsupervised Learning and non-Parametric methods 38 h January - February
Sebastian Goldt Neural Networks 36 h January - March
Sebastian Goldt Current topics in the theory of neural networks: Dynamics and Data 42 h April - June 7
Roberto Trotta Current topics in the theory of neural networks: Dynamics and Data 42 h April - June 7
Guido Sanguinetti Machine learning applications to single-cell genomics 42 h April - June 7
Luca Bortolussi, Giulio Caravagna, Luca Manzoni, Lorenzo Castelli Scientific Computing and Algorithms 36 h TBA 6

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