Introduction to Computational Thinking〈1st ed.〉 : Problem Solving, Algorithms, Data Structures, and More

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  • 電子書籍
  • ポイントキャンペーン

Introduction to Computational Thinking〈1st ed.〉 : Problem Solving, Algorithms, Data Structures, and More

  • 著者名:Mailund, Thomas
  • 価格 ¥15,130 (本体¥13,755)
  • Apress(2021/07/16発売)
  • 麗しの桜!Kinoppy 電子書籍・電子洋書 全点ポイント25倍キャンペーン(~3/29)
  • ポイント 3,425pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9781484270769
  • eISBN:9781484270776

ファイル: /

Description

Learn approaches of computational thinking and the art of designing algorithms. Most of the algorithms you will see in this book are used in almost all software that runs on your computer.

Learning how to program can be very rewarding. It is a special feeling to seeing a computer translate your thoughts into actions and see it solve your problems for you. To get to that point, however, you must learn to think about computations in a new way—you must learn computational thinking.

This book begins by discussing models of the world and how to formalize problems. This leads onto a definition of computational thinking and putting computational thinking in a broader context. The practical coding in the book is carried out in Python; you’ll get an introduction to Python programming, including how to set up your development environment.

What You Will Learn

  • Think in a computational way
  • Acquire general techniques for problem solving
  • Seegeneral and concrete algorithmic techniques
  • Program solutions that are both computationally efficient and maintainable

Who This Book Is For 

Those new to programming and computer science who are interested in learning how to program algorithms and working with other computational aspects of programming.

Table of Contents

1: Introduction.- 2: Introducing Python Programming.- 3: Introduction to Algorithms.- 4: Algorithmic Efficiency.- 5: Searching and Sorting.- 6: Functions.- 7: Inner Functions.- 8: Recursion.- 9: Divide and Conquer and Dynamic Programming.- 10: Hidden Markov Models.- 11: Data Structures, Objects and Classes.- 12: Class Hierarchies and Inheritance.- 13: Sequences.- 14: Sets.- 15: Red-black Search Trees.- 16: Stacks and Queues.- 17: Priority Queues.- 18: Conclusions.

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