Students were introduced to different types of inference; how data science models relate to rules, causes, and effects; how the data science process can begin with either a focused question or with data; concepts relating to balancing use cases, models, and data; and how data wrangling and feature engineering fit in the data science pipeline, with a live demo of AWS SageMaker with NY Fed mortgage debt and delinquency data.