This document provides an introduction to data science. It defines a data scientist as someone who is inquisitive and explores data by asking questions and testing assumptions. It recommends useful Python libraries for data science like Pandas, scikit-learn, SciPy, and NumPy. It also recommends tools like Jupyter, Rodeo IDE, Canopy IDE, and the Caravel application. Finally, it provides some top free online courses and references for getting started in data science.