Applied Computational Thinking with Python
Applied Computational Thinking with Python

Author: Sofía De Jesús

Publisher: Packt Publishing Ltd

Published: 2020-11-27

Total Pages: 420

ISBN-13: 183921676X

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Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains Key FeaturesDevelop logical reasoning and problem-solving skills that will help you tackle complex problemsExplore core computer science concepts and important computational thinking elements using practical examplesFind out how to identify the best-suited algorithmic solution for your problemBook Description Computational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development. What you will learnFind out how to use decomposition to solve problems through visual representationEmploy pattern generalization and abstraction to design solutionsBuild analytical skills required to assess algorithmic solutionsUse computational thinking with Python for statistical analysisUnderstand the input and output needs for designing algorithmic solutionsUse computational thinking to solve data processing problemsIdentify errors in logical processing to refine your solution designApply computational thinking in various domains, such as cryptography, economics, and machine learningWho this book is for This book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.

Applied Computational Thinking with Python
Applied Computational Thinking with Python

Author: Sofía De Jesús

Publisher: Packt Publishing Ltd

Published: 2023-12-29

Total Pages: 438

ISBN-13: 1837631085

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Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains Key Features Develop logical reasoning and problem-solving skills that will help you tackle complex problems Explore core computer science concepts and important computational thinking elements using practical examples Find out how to identify the best-suited algorithmic solution for your problem Book DescriptionComputational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development.What you will learn Find out how to use decomposition to solve problems through visual representation Employ pattern generalization and abstraction to design solutions Build analytical skills to assess algorithmic solutions Use computational thinking with Python for statistical analysis Understand the input and output needs for designing algorithmic solutions Use computational thinking to solve data processing problems Identify errors in logical processing to refine your solution design Apply computational thinking in domains, such as cryptography, and machine learning Who this book is for This book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.

Head First Learn to Code
Head First Learn to Code

Author: Eric Freeman

Publisher: "O'Reilly Media, Inc."

Published: 2018-01-02

Total Pages: 1033

ISBN-13: 1491958812

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What will you learn from this book? Itâ??s no secret the world around you is becoming more connected, more configurable, more programmable, more computational. You can remain a passive participant, or you can learn to code. With Head First Learn to Code youâ??ll learn how to think computationally and how to write code to make your computer, mobile device, or anything with a CPU do things for you. Using the Python programming language, youâ??ll learn step by step the core concepts of programming as well as many fundamental topics from computer science, such as data structures, storage, abstraction, recursion, and modularity. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Learn to Code uses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

Introduction to Computational Thinking
Introduction to Computational Thinking

Author: Thomas Mailund

Publisher: Apress

Published: 2021-07-31

Total Pages: 657

ISBN-13: 9781484270769

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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 See general 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.

A Primer on Scientific Programming with Python
A Primer on Scientific Programming with Python

Author: Hans Petter Langtangen

Publisher: Springer

Published: 2016-07-28

Total Pages: 942

ISBN-13: 3662498871

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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Introduction to Python Programming
Introduction to Python Programming

Author: Gowrishankar S

Publisher: CRC Press

Published: 2018-12-07

Total Pages: 410

ISBN-13: 1351013211

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Introduction to Python Programming is written for students who are beginners in the field of computer programming. This book presents an intuitive approach to the concepts of Python Programming for students. This book differs from traditional texts not only in its philosophy but also in its overall focus, level of activities, development of topics, and attention to programming details. The contents of the book are chosen with utmost care after analyzing the syllabus for Python course prescribed by various top universities in USA, Europe, and Asia. Since the prerequisite know-how varies significantly from student to student, the book’s overall overture addresses the challenges of teaching and learning of students which is fine-tuned by the authors’ experience with large sections of students. This book uses natural language expressions instead of the traditional shortened words of the programming world. This book has been written with the goal to provide students with a textbook that can be easily understood and to make a connection between what students are learning and how they may apply that knowledge. Features of this book This book does not assume any previous programming experience, although of course, any exposure to other programming languages is useful This book introduces all of the key concepts of Python programming language with helpful illustrations Programming examples are presented in a clear and consistent manner Each line of code is numbered and explained in detail Use of f-strings throughout the book Hundreds of real-world examples are included and they come from fields such as entertainment, sports, music and environmental studies Students can periodically check their progress with in-chapter quizzes that appear in all chapters

HT THINK LIKE A COMPUTER SCIEN
HT THINK LIKE A COMPUTER SCIEN

Author: Jeffrey Elkner

Publisher: Samurai Media Limited

Published: 2016-10-04

Total Pages: 306

ISBN-13: 9789888406784

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The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.

Essential Computational Thinking
Essential Computational Thinking

Author: Ricky J. Sethi

Publisher: Cognella Academic Publishing

Published: 2020-06-17

Total Pages: 328

ISBN-13: 1516583213

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Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science. Rooted in fundamental science, this text defines elementary ideas including data and information, quantifies these ideas mathematically, and, through key concepts in physics and computation, demonstrates the relationship between computer science and the universe itself. In Part I, students explore the theoretical underpinnings of computer science in a wide-ranging manner. Readers receive a robust overview of essential computational theories and programming ideas, as well as topics that examine the mathematical and physical foundations of computer science. Part 2 presents the basics of computation and underscores programming as an invaluable tool in the discipline. Students can apply their newfound knowledge and begin writing substantial programs immediately. Finally, Part 3 explores more sophisticated computational ideas, including object-oriented programing, databases, data science, and some of the underlying principles of machine learning. Essential Computational Thinking is an ideal text for a firmly technical CS0 course in computer science. It is also a valuable resource for highly-motivated non-computer science majors at the undergraduate or graduate level who are interested in learning more about the discipline for either professional or personal development.

Effective Computation in Physics
Effective Computation in Physics

Author: Anthony Scopatz

Publisher: "O'Reilly Media, Inc."

Published: 2015-06-25

Total Pages: 567

ISBN-13: 1491901586

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More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures