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Introduction To Computation And Programming Using Python, Second Edition: With Application To Understanding Data,Used
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The New Edition Of An Introductory Text That Teaches Students The Art Of Computational Problem Solving, Covering Topics Ranging From Simple Algorithms To Information Visualization.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 (Mooc). This New Edition Has Been Updated For Python 3, Reorganized To Make It Easier To Use For Courses That Cover Only A Subset Of The Material, And Offers Additional Material Including Five New Chapters.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. 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. This Edition Offers Expanded Material On Statistics And Machine Learning And New Chapters On Frequentist And Bayesian Statistics.
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- Q: How many pages does this book have? A: This book has four hundred sixty-six pages. It provides comprehensive coverage of computational problem solving and programming using Python.
- Q: What are the dimensions of this book? A: The book measures seven point zero one inches in length, zero point eight four inches in width, and eight point nine four inches in height. These dimensions make it a handy reference for students.
- Q: What type of binding does this book have? A: This book is paperback bound. The paperback format makes it lightweight and portable for easy reading.
- Q: What is the reading level of this book? A: This book is suitable for beginners and those with little or no prior programming experience. It is designed to introduce students to computational problem solving.
- Q: Is this book suitable for self-study? A: Yes, this book is suitable for self-study. It was developed for use in massive open online courses, making it ideal for independent learners.
- Q: How can I apply what I learn from this book? A: You can apply the concepts learned from this book in various programming and data science projects. It covers practical techniques for modeling and interpreting data.
- Q: Can I use this book for a classroom setting? A: Yes, this book is designed for classroom use. It is based on a popular MIT course and is suitable for both conventional and online learning environments.
- Q: What programming language does this book focus on? A: This book focuses on the Python programming language. It introduces students to Python and various libraries used for computational problem solving.
- Q: Does this book cover advanced topics? A: Yes, the book includes advanced topics like optimization problems and dynamic programming. It also offers expanded material on statistics and machine learning.
- Q: How should I care for this book? A: To care for this book, store it in a cool, dry place and avoid exposing it to moisture. Keeping it away from direct sunlight will prevent fading.
- Q: Is this book safe for kids? A: Yes, this book is safe for kids, particularly those interested in learning programming. It is educational and introduces fundamental concepts in a clear manner.
- Q: What if my book arrives damaged? A: If your book arrives damaged, contact the seller for a return or exchange. Most retailers have policies in place for handling damaged items.
- Q: Is there a warranty for this book? A: Books typically do not come with a warranty. However, check the return policy of the retailer from whom it was purchased for further information.
- Q: Can I find similar books on this topic? A: Yes, there are many books on computational problem solving and programming. Look for titles focused on Python and data science for similar content.
- Q: What is the author's background? A: The author of this book is John V. Guttag, a professor at MIT. He has extensive experience in teaching computer science and programming.
- Q: Are there any online resources that complement this book? A: Yes, the book is based on an MIT course offered through MIT's OpenCourseWare, which includes online resources and lectures that complement the material.