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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

Chapter 2: Elements of Computational Thinking

The previous chapter provided some general information about the fundamentals of computer science. In this chapter, we will focus more closely on understanding computational thinking and the elements that make up computational thinking: decomposition, pattern recognition, pattern generalization or abstraction, and algorithm design.

The importance of the computational thinking process cannot be understated. Through the process, we analyze problems to design the best possible solutions based on a set of conditions. Although many algorithms can be written to answer the same questions, using the computational thinking process helps us to determine the optimal path to take to design a clear algorithm that can be generalized.

In this chapter, we will cover the following topics:

  • Understanding computational thinking
  • Decomposing problems
  • Recognizing patterns
  • Generalizing patterns
  • Designing algorithms
  • Additional...
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