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 PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, 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, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

作者簡介：

John V. Guttag

1999年至2004年任麻省理工學院電氣工程與計算機科學係主任（此前擔任瞭5年的副主任）。Guttag教授目前是計算機科學與人工智能實驗室網絡及移動係統組的聯閤負責人。此外，他還進行軟件工程、機器定理證明、硬件驗證等領域的研究以及培訓工作，並齣版過相關主題的圖書。Guttag教授獲得美國布朗大學英語專業學士學位、應用數學碩士學位，獲得多倫多大學計算機科學博士學位。

譯者簡介：

梁傑

北京航空航天大學計算機科學與技術專業大四學生。熱愛開源、JavaScript、Python，喜歡做各種各樣有趣的事情。