Day 1

On April 21 at 4 PM, we held a video tutorial session with 154 participants for those in the Brown community and beyond. We used Pandas to explore one of the most popular COVID-19 data sets, and we discussed some approaches to prediction.

We used a platform called Babylon House to enable interactivity via chat. A Google Colab notebook with the Babylon House script and code, as well as the video recording, are available here:

A Brown login is required to watch the video, but the Colab notebook is recommended as the more efficient source anyway.

Day 2

On 12 PM on Friday, June 5, we discussed methods for estimating the crucially important quantity Rₜ (the average number of new infections generated by each infectious individual, at time t).

Day 3

Next time, Friday, June 19 at 12 PM Eastern Time, we continued our discussion of Rₜ estimation (though developed the content in a way which facilitates participation for those who didn’t attend Day 2).

The content from this session is available at this GitHub repo.

The Babylon House link is the same as for the previous meetings, and the Zoom link is here.