Computational Thinking For The Modern Problem Solver

Through examples and analogies, Computational Thinking for the Modern Problem Solver introduces computational thinking as part of an introductory computing course and shows how computer science concepts are applicable to other fields. It keeps the material accessible and relevant to noncomputer science majors. With numerous color figures, this classroom-tested book focuses on both foundational computer science concepts and engineering topics. It covers abstraction, algorithms, logic, graph theory, social issues of software, and numeric modeling as well as execution control, problem-solving strategies, testing, and data encoding and organizing. The text also discusses fundamental concepts of programming, including variables and assignment, sequential execution, selection, repetition, control abstraction, data organization, and concurrency. The authors present the algorithms using language-independent notation.

Through examples and analogies, Computational Thinking for the Modern Problem Solver introduces computational thinking as part of an introductory computing course and shows how computer science concepts are applicable to other fields. It keeps the material accessible and relevant to noncomputer science majors. With numerous color figures, this classroom-tested book focuses on both foundational computer science concepts and engineering topics. It covers abstraction, algorithms, logic, graph theory, social issues of software, and numeric modeling as well as execution control, problem-solving strategies, testing, and data encoding and organizing. The text also discusses fundamental concepts of programming, including variables and assignment, sequential execution, selection, repetition, control abstraction, data organization, and concurrency. The authors present the algorithms using language-independent notation.

Computational Thinking (CT) involves fundamental concepts and reasoning, distilled from computer science and other computational sciences, which become powerful general mental tools for solving problems, increasing efficiency, reducing complexity, designing procedures, or interacting with humans and machines. An easy-to-understand guidebook, From Computing to Computational Thinking gives you the tools for understanding and using CT. It does not assume experience or knowledge of programming or of a programming language, but explains concepts and methods for CT with clarity and depth. Successful applications in diverse disciplines have shown the power of CT in problem solving. The book uses puzzles, games, and everyday examples as starting points for discussion and for connecting abstract thinking patterns to real-life situations. It provides an interesting and thought-provoking way to gain general knowledge about modern computing and the concepts and thinking processes underlying modern digital technologies.

An introduction to computational thinking that traces a genealogy beginning centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview, tracing a genealogy that begins centuries before digital computers and portraying computational thinking as pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. The authors identify six dimensions of today's highly developed CT—methods, machines, computing education, software engineering, computational science, and design—and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.

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.

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.

The cultural, social, and economic history of mankind is characterized by a succession of needs and problems that have stimulated the invention of operational and conceptual tools to facilitate their solution. The continuous presentation of new needs, an attempt to improve partial solutions to old problems, curiosity, and the disinterested search for knowledge then constituted the fundamental push for scientific, cultural, economic, and social progress. In an increasingly digital society, where software technological tools permeate daily life and, consequently, change the management of reality, mastering of transversal skills is crucial for success. Computational thinking is a set of transversal skills related to the foundations of computer science as a scientific discipline and means a mastering to the process of solving problems. The goal of computational thinking is to acquire interpretative perspectives of reality, which allows one to read the digital experience competently and responsibly. Computational Thinking for Problem Solving and Managerial Mindset Training explores how individuals can be trained into managerial mindsets through computational thinking and computer science. It explores how computer science can be used as a valid guideline to develop skills such as effective soft skills, communication skills, and collaboration. Further, the chapters explore the adoption of computational thinking for individuals to gain managerial mindsets and successfully solve questions and problems in their domain of interest. This will include artificial intelligence applications, strategic thinking, management training, ethics, emergency managerial mindsets, and more. This book is valuable for managers, professionals, practitioners, researchers, academicians, and students interested in how computational thinking can be applied for the training of managerial mindsets.

Computational thinking (CT) is a timeless, transferable skill that enables you to think more clearly and logically, as well as a way to solve specific problems. With this book you'll learn to apply computational thinking in the context of software development to give you a head start on the road to becoming an experienced and effective programmer.