Presented By: The Center for the Study of Complex Systems
Computational Social Science Methods Workshop - "Causal inference in online systems: Methods, pitfalls and best practices"
Amit Sharma, Microsoft Research, India
TO REGISTER - CLICK THE 'REGISTER HERE' LINK IN THE BOX BELOW, AND THEN THE 'LUNCH CHOICE' LINK BELOW THAT.
A hands-on introduction to causal inference with a focus on applying it to socio-technical systems. By working with code in Python, participants will learn about different approaches to causal inference, including randomized experiments, natural experiments such as instrumental variables, and observational methods such as matching. Throughout, we will try to make connections with counterfactual reasoning, machine learning, and past work in the social sciences.
Registration is limited to 30 persons.
Participation Limited to Faculty, Staff, Postdoctoral Fellows and Graduate Students
A hands-on introduction to causal inference with a focus on applying it to socio-technical systems. By working with code in Python, participants will learn about different approaches to causal inference, including randomized experiments, natural experiments such as instrumental variables, and observational methods such as matching. Throughout, we will try to make connections with counterfactual reasoning, machine learning, and past work in the social sciences.
Registration is limited to 30 persons.
Participation Limited to Faculty, Staff, Postdoctoral Fellows and Graduate Students
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