Ten simple rules for organizing a data science workshop

[...]Rule 10 focuses on the importance of continuously evaluating and learning from past workshops to inform future pedagogy. The breadth of knowledge required and cognitive biases of a single person could derail a workshop entirely. [...]the organization and planning of such workshops necessitate collaboration, as the perspective of different people typically allows to develop a more inclusive training material. Connecting learning objectives from different training modules taught by different instructors requires a large effort in coordination and communication. [...]a person should be designated as the overall coordinator to ensure learning objectives from individual training modules are connected. [...]the workshop coordinator should ensure each session and learning objectives build toward the overall vision and goals of the workshop (Rule 1).