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Livestream Seminar

Machine Learning for Estimating Causal Effects

A 4-Day Livestream Seminar Taught by

Ashley Naimi
Course Dates:

Tuesday, June 14, 2022 –
Friday, June 17, 2022

Schedule:

10:30am-12:30pm ET (New York time): Live session via Zoom
1:30pm-3:00pm ET: Live session via Zoom

Machine learning is increasingly being used to evaluate cause-effect relations with social, economic, health, and business data. When used properly, these tools have tremendous potential to yield robust effect estimates with minimal assumptions. However, both machine learning and causal inference techniques add considerable complexity to an analysis, making proper use a challenge.

In this seminar, you will learn how to minimize biases that result from improper use of machine learning methods to answer practical questions about cause-effect relations in non-experimental data.

Starting June 14, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. Participants are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if they are unable to attend at the scheduled time

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

Closed captioning is available for all live and recorded sessions.

More details about the course content

Computing

Who should register?

Seminar outline

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