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Applied Computational Thinking with Python

You're reading from   Applied Computational Thinking with Python Design algorithmic solutions for complex and challenging real-world problems

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781839219436
Length 420 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Dayrene Martinez Dayrene Martinez
Author Profile Icon Dayrene Martinez
Dayrene Martinez
Sofía De Jesús Sofía De Jesús
Author Profile Icon Sofía De Jesús
Sofía De Jesús
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Introduction to Computational Thinking
2. Chapter 1: Fundamentals of Computer Science FREE CHAPTER 3. Chapter 2: Elements of Computational Thinking 4. Chapter 3: Understanding Algorithms and Algorithmic Thinking 5. Chapter 4: Understanding Logical Reasoning 6. Chapter 5: Exploring Problem Analysis 7. Chapter 6: Designing Solutions and Solution Processes 8. Chapter 7: Identifying Challenges within Solutions 9. Section 2:Applying Python and Computational Thinking
10. Chapter 8: Introduction to Python 11. Chapter 9: Understanding Input and Output to Design a Solution Algorithm 12. Chapter 10: Control Flow 13. Chapter 11: Using Computational Thinking and Python in Simple Challenges 14. Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python
15. Chapter 12: Using Python in Experimental and Data Analysis Problems 16. Chapter 13: Using Classification and Clusters 17. Chapter 14: Using Computational Thinking and Python in Statistical Analysis 18. Chapter 15: Applied Computational Thinking Problems 19. Chapter 16: Advanced Applied Computational Thinking Problems 20. Other Books You May Enjoy

Preface

Applied Computational Thinking with Python provides a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time. Developers working with Python will be able to put their knowledge to work with this practical guide using the computational thinking method for problem solving.

This book will help 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 practice solving problems in multiple areas, including economics, mathematics, and artificial intelligence.

The 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.

We'll find out how to use decomposition for solving problems through visual representation. We'll also employ pattern generalization and abstraction for designing solutions and building the analytical skills required to assess algorithmic solutions. We'll also use computational thinking with Python for statistical analyses.

We will understand the input and output requirements in terms of designing algorithmic solutions, and use computational thinking to solve data processing problems. We'll identify errors in logical processing to refine your solution design and apply computational thinking in various domains, such as cryptography, economics, and machine learning.

You'll then learn about the various techniques involved in problem analysis, logical reasoning, algorithm design, classification and clusters, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions.

We'll also develop logical reasoning and problem-solving skills that will help you tackle complex problems. We'll also explore core computer science concepts and important computational thinking elements using practical examples and find out how to identify the algorithmic solution that is best-suited to your problem.

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 apply computational thinking techniques to software development.

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