Brief Summary; Causality is central to the understanding and use of data. Without an understanding of cause-effect relationships, we cannot use data to answer questions as basic as “Does this treatment harm or help patients?” . The course presents causal networks by first providing basics probability and introducing graphical models. Then, the problem of predicting the effect of interventions is presented and discussed. Finally, counterfactuals and their applications are presented.

Schedule

• 2021 September 06th, 10:00-12:00
• 2021 September 08th, 14:00-16:00
• 2021 September 09th, 10:00-12:00
• 2021 September 10th, 10:00-12:00
• 2021 September 13th, 10:00-12:00
• 2021 September 17th, 10:00-12:00
• 2021 September 20th, 10:00-12:00
• 2021 September 22nd, 10:00-12:00
• 2021 September 24th, 10:00-12:00
• 2021 September 27th, 10:00-12:00
• 2021 September 29th, 10:00-12:00
• 2021 October 01st, 10:00-12:00

Due to the pandemic and according to Administrative rules, all lectures, initially expected to be delivered in presence, will take place on streaming, in my Personal WebEx Room

https://unimib.webex.com/meet/fabio.stella

Exam; by the end of the course, teachers will assign a paper to each group of students (4 members). Each group must deliver an oral presentation of 20 minutes (each member has to present).

Teachers; Luca Bernardinello, Fabio Stella and Peter Lucas