Based on an MIT massive open online course (MOOC), this book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. This third edition expands the initial explanatory material, making it a gentler introduction to programming for the beginner, with more programming examples and many more "finger exercises." A new chapter shows how to use the pandas package for analyzing time series data. All the code has been rewritten to make it stylistically consistent with the PEP 8 standards. In addition to covering traditional topics, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, statistical techniques that inform (and misinform), and optimization problems and dynamic programming. The book also includes a Python 3 quick reference guide. Book jacket.