Lecture, three hours; discussion, one hour. Requisites: courses 203A, 203B, 212A. Introduction to data science tools in Python. Topics include Python programming, Jupyter Notebook for literate programming, NumPy and SciPy for scientific computing, pandas for data analysis and manipulation, Matplotlib and other libraries for data visualization, scikit-learn for machine learning, and deep learning libraries. S/U or letter grading.