Applied Computational Thinking with Python
eBook - ePub

Applied Computational Thinking with Python

Design algorithmic solutions for complex and challenging real-world problems

  1. 420 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Applied Computational Thinking with Python

Design algorithmic solutions for complex and challenging real-world problems

About this book

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 required 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 various domains, such as cryptography, economics, 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.

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Yes, you can access Applied Computational Thinking with Python by Sofía De Jesús,Dayrene Martinez in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

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