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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 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.
- Sales Rank: #51914 in Books
- Brand: Brand: The MIT Press
- Published on: 2013-08-09
- Original language: English
- Number of items: 1
- Dimensions: 11.00" h x .50" w x 8.50" l, 1.65 pounds
- Binding: Paperback
- 320 pages
- Used Book in Good Condition
Review
This is the 'computational thinking' book we have all been waiting for! With humor and historical anecdotes, John Guttag conveys the breadth and joy of computer science without compromise to technical detail. This book is perfect for any student who wants to explore the essence of computer science.
(Jeannette M. Wing, President's Professor of Computer Science and Department Head, Carnegie Mellon University)John Guttag is an extraordinary teacher and an extraordinary writer. (Perhaps having been an undergraduate English major -- an uncommon stepping stone to the leadership of the world's top EECS department -- has something to do with this.) This is not 'a Python book' -- although you will learn Python. Nor is it a 'programming book' -- although you will learn to program. It is a rigorous but eminently readable introduction to computational problem solving.
(Ed Lazowska, Bill & Melinda Gates Chair in Computer Science & Engineering, University of Washington)There's no such thing as the only computer science book you'll ever need. But if you had to pick only one, this would be a great choice. You'll begin by getting a solid introduction to programming in Python. Armed with that, you'll go hands-on with important computing ideas like random methods, statistics, and optimization, using tools of great theoretical beauty and great practical importance.
(Hal Abelson, coauthor (with Gerald Jay Sussman) of Structure and Interpretation of Computer Programs) About the Author
John V. Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT.
Most helpful customer reviews
53 of 55 people found the following review helpful.
Excellent book
By Mike K
Let me post a disclaimer first. I bought the paperback from MIT-press' website since it was cheaper after the edX discount.
Now the real deal : The book is excellent. It is the perfect companion to MIT's course on edX. I attended the course on a whim, since I already have a masters degree in computer engineer, but I thoroughly enjoyed it. The book takes a beginner from the basics to some of the most important aspects of computer science. There is a bit of graph theory, a bit of statistics, a bit of sorting, linear regression, data plotting using Pylab, and even the knapsack problem thrown in. I loved the book as well as the course, and will readily recommend both to people interested in computer science, irrespective of the level of their expertise (there is something for everyone).
I have read bad reviews about the Kindle edition of this book and so I will add that a DRM free e-book is also available for purchase from MIT-press' website. If you want the ability to open your e-book with any PDF reader, buy that instead of the Kindle version.
36 of 37 people found the following review helpful.
Five Stars for Sure, but only 1/3 about Python, mostly Algorithms and how to handle computational complexity.
By David S. Day
Bought this for the MIT Computer Science course 6.00.1x. It is a fast paced but very readable first year text for Computer Science. It uses Python 2.X as its language and you will come up to speed in Python quickly, and then spend the bulk of the book learning algorithms and computational techniques.
I am very pleased with the book. It is terse and fast. If you require a more leisurely pace, John Zelle's Python Programming, an Introduction to Computer Science takes 425 pages to cover what this book covers in 110 pages, and then has a short chapter just touching on what this book covers more deeply in the remaining 200 pages. Zelle's book is also a popular first year CS text, but obviously for a different audience. Obviously, you will learn more with this book if you can take the pace. I bought Zelle's book also and have used it for extra exercises and the occasional alternative explanation.
I also am using Problem Solving with Algorithms and Data Structures by Miller and Ranum to supplement/flesh out my algorithms knowledge during breaks in the class. This also seems to be a good book, and uses Python as its language for examples.
Buy Guttag for sure, or Zelle if you feel the need for a slower pace, and Miller and Ranum to flesh out your algorithms.
Dave
27 of 29 people found the following review helpful.
Too Much Prose
By Jonathan Marsan
Taking the edX class. I thought this book would help and it does: it repeats the content of the class, but adds very little. My issue with the book is that: 1) It isn't easy to search. 2) It covers concepts too quickly - very little review. 3) Programming terminology is "bolded", but no glossary is provided at the back.
I recommend the book to those taking the edX class simply because it helps reduce note-taking. But if you are a beginner at programming and just looking for a book to start learning Python, I am sure there are better ones out there (i.e. clearer books that are a little more "hands-on"). I have enjoyed learning web related languages with Sitepoint and O'reilly books, so I'll probably look into getting one of those to deepen my understanding of Python.
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