Minicourse: Signals, optima and sparse structures: the Python way. !!!MODIFIED TIMETABLE!!!

Bringing state-of-the-art mathematical tools into data science is a highly appreciated ability both in industry and applied research. During the minicourse the participant will be introduced to some classical problems of signal processing, namely filtering, denoising, sparse recovery and convex optimisation. All the issues will be addressed both from the theoretical and the algorithmic point of view.

Schedule:
May, 7: 2.00pm-3.30pm, room M (installation of python packages)
May, 8: 1.00pm-2.30pm, " (lunch allowed during the class)
May, 9: 9.30am-11.00aa, meeting room second floor
May, 10: 2.00pm-3.30pm, "
May, 11: 11.30am-1.00pm, "
May, 11: 3.30pm-5.00pm, meeting room ground floor.