Eugene Yan's essay "How to Give a Kick-Ass Data Science Talk" is a first-person guide rooted in five years of speaking at and hosting meet-ups. It addresses both sides of the equation: why a data scientist should give a talk, and how to do it well. The advice is aimed at practitioners who may not see public speaking as a core part of their role.
The essay is practical in tone and draws on the author's own experience rather than academic research or survey data. It does not present competing viewpoints; the recommendations come from one practitioner's repeated exposure to both giving talks and organizing events. For readers in AI and ML, the relevance is direct: technical work often needs to be explained to mixed audiences, and talks are one way to practice that skill.