In this interactive workshop, participants are introduced to data cleaning, where it fits into a typical machine learning workflow and the importance of cleaning data. Participants will then learn about the common issues that make a dataset “dirty” and the learn various ways that data scientists deal with them.  Throughout this workshop, participants will have the opportunity to actively engage as they observe and follow the transformation of a contaminated dataset into a refined and usable form.

By the end of the workshop, participants should be confident applying the various data cleaning techniques taught and clean their own data for their own data science projects.