An introduction to data science and data science life cycle focusing on the exploratory data analysis (EDA) phase. Datasets used for the EDA will be drawn from social justice issues.  Topics include introduction to data science and its life cycle, missing data and how to address them, biases in data collection and training, data pre-processing, learning to ask questions of the data, data visualization through explorations with no-code tools (for example, spreadsheets, CODAP, etc.), discovering patterns and anomalies in the data, composing stories told by the data through simple hypothesis testing and simple regression modeling, and writing reproducible reports.