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Introduction to computational thinki...

Mailund, Thomas.

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Introduction to computational thinking = problem solving, algorithms, data structures, and more /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to computational thinking/ by Thomas Mailund.
其他題名:	problem solving, algorithms, data structures, and more /
作者:	Mailund, Thomas.
出版者:	Berkeley, CA :Apress : : 2021.,
面頁冊數:	xiii, 657 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Algorithms. -
電子資源:	https://doi.org/10.1007/978-1-4842-7077-6
ISBN:	9781484270776

Introduction to computational thinking = problem solving, algorithms, data structures, and more /
Mailund, Thomas.

Introduction to computational thinkingproblem solving, algorithms, data structures, and more /[electronic resource] :by Thomas Mailund. - Berkeley, CA :Apress :2021. - xiii, 657 p. :ill., digital ;24 cm.

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.

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. You will: Think in a computational way Acquire general techniques for problem solving See general and concrete algorithmic techniques Program solutions that are both computationally efficient and maintainable.

ISBN: 9781484270776

Standard No.: 10.1007/978-1-4842-7077-6doiSubjects--Topical Terms:

536374
Algorithms.

LC Class. No.: QA76.73.P98 / M35 2021

Dewey Class. No.: 005.133

Introduction to computational thinking = problem solving, algorithms, data structures, and more /
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505 0 $a 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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