Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

This two-part series will focus on how to set up database-like structures, navigate them, create models and build various types of reports in Microsoft Excel. By the end of this series, participants will be able to sort and look for information within large datasets, use character-based functions, pivot tables, and build basic financial models.

Technology requirement: Please arrive with Microsoft Excel installed on your laptop.