nach der Bestellung gedruckt Neuware - Printed after ordering - Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domainsKey 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 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 learnFind out how to use decomposition to solve problems through visual representationEmploy pattern generalization and abstraction to design solutionsBuild analytical skills 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 domains, such as cryptography, and machine learningWho this book is forThis 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.Table of ContentsFundamentals of Computer ScienceElements of Computational ThinkingUnderstanding Algorithms and Algorithmic ThinkingUnderstanding Logical ReasoningErrorsExploring Problem AnalysisDesigning Solutions and Solution ProcessesIdentifying Challenges within SolutionsIntroduction to PythonUnderstanding Input and Output to Design a Solution AlgorithmControl FlowUsing Computational Thinkning and Python in Simples ChallengesDebuggingUsing Python in Experimental and Data AnalysisUsing Classification and Clusters Introduction to Machine LearningUsing Computational Thinking and Pythin in Statistical AnalysisApplied Computational Thinking ProblemsAdvanced Applied Computational Thinking ProblemsUsage of Cloud Platforms.

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Detalles bibliogr�ficos

T�tulo: Applied Computational Thinking with Python - Second Edition : Algorithm design for complex real-world problems
Editor: Packt Publishing
Fecha de publicaci�n: 2023
Idioma: Ingl�s
ISBN 10: 1837632308
ISBN 13: 9781837632305
Encuadernaci�n: Taschenbuch
Edici�n: 2� Edici�n
Estado: Neu
Dimensiones: 235�mil�metros de ancho por 191 de alto por 24 de largo
Peso: 813 gramos

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Sinopsis

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 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 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.

Fundamentals of Computer Science
Elements of Computational Thinking
Understanding Algorithms and Algorithmic Thinking
Understanding Logical Reasoning
Errors
Exploring Problem Analysis
Designing Solutions and Solution Processes
Identifying Challenges within Solutions
Introduction to Python
Understanding Input and Output to Design a Solution Algorithm
Control Flow
Using Computational Thinkning and Python in Simples Challenges
Debugging
Using Python in Experimental and Data Analysis
Using Classification and Clusters Introduction to Machine Learning
Using Computational Thinking and Pythin in Statistical Analysis
Applied Computational Thinking Problems
Advanced Applied Computational Thinking Problems
Usage of Cloud Platforms

Acerca de los autores

Sof�a De Jes�s is a computational thinking teacher with a degree from the University of Puerto Rico with a focus on math. She has a master's degree from the University of Dayton. Her experience in education and development spans two decades. She has worked with clients to develop solutions in multiple programming languages. As a teacher, Sof�a helps students incorporate the philosophy of computational thinking in courses like game design, circuits, Python, web design, and robotics. She likes to play video games and spend time with her 11 year old Yorkie, King Kong. Sof�a also enjoys creating materials, small furniture, and jewelry using CNC machines and laser cutters. She enjoys spending as much time in Puerto Rico as work and life permits.

Dayrene Martinez is a data engineer specializing in AI at one of the Big Four consulting firms. She holds a bachelor's degree in electrical engineering. Her expertise includes optimizing neural network models, ETL and AWS cloud computing. Previously, she was a systems engineer in the defense industry, developing neural networks for aerospace vehicle decision-making. Dayrene is a dedicated and passionate engineer who serves as a keynote speaker and mentor inspiring high school students, college students, and career changers in engineering and tech by sharing her experiences and insights, making a positive impact on the next generation of talent in the field.

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