How To Train Algorithmic Thinking
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Anyone Can Code: Algorithmic Thinking
As the second book in the Anyone Can Code series, Algorithmic Thinking focuses on the logic behind computer programming and software design. With a data-centred approach, it starts with simple algorithms that work on simple data items and advances to more complex ones covering data structures and classes. Examples are given in C/C++ and Python and use both plain text and graphics applications to illustrate the concepts in different languages and forms. With the advances in artificial intelligence and automated code generators, it is essential to learn about the logic of what a code needs to do, not just how to write the code. Anyone Can Code: Algorithmic Thinking is suitable for anyone who aims to improve their programming skills and go beyond the simple craft of programming, stepping into the world of algorithm design. This book is independent of the first one in the series but assumes some basic familiarity with programming, such as language syntax.
Revolutionizing Curricula Through Computational Thinking, Logic, and Problem Solving
In today's rapidly evolving educational landscape, traditional teaching methods often fail to equip students with the skills necessary for success in the 21st century. The siloed approach to education, where subjects are taught in isolation, must reflect the interconnected nature of modern challenges. This disconnect between traditional educational models and the needs of the future workforce is a serious concern among educators. They face the challenge of preparing students for professions that still need to be created using tools and technologies that are still emerging. Revolutionizing Curricula Through Computational Thinking, Logic, and Problem Solving offers a transformative solution to this challenge. By advocating for computational thinking as a fundamental skill set applicable across all academic disciplines, the book provides educators with the tools to bridge this gap. It introduces computational thinking not just as a technical skill but as a way of problem-solving and logical reasoning that enhances critical thinking across subjects. Through practical lesson plans, case studies, and strategies, educators can seamlessly integrate computational thinking into their classrooms, preparing students for the complexities of the modern world.
Applied Computational Thinking with Python
Author: Sofía De Jesús
language: en
Publisher: Packt Publishing Ltd
Release Date: 2020-11-27
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.