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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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Toc

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

Summary

In this chapter, we discussed the definition of an algorithm, which is a set of steps that allows a computer to complete a process and provide some output. We went through the characteristics of algorithms.

We designed algorithms based on problem scenarios and then analyzed algorithms to determine whether they met the characteristics needed to run properly. Understanding the characteristics of algorithms and how algorithms work will allow us to create algorithms with far fewer errors than if we were unaware of these characteristics. Notice that I said fewer errors.

When working with code, errors are a fact of life. We will inevitably make mistakes and we will accidentally introduce bugs or make some code infinite. Understanding the characteristics of a good algorithm allows us to reduce those errors, even if we don't fully eliminate them from our daily lives.

In the next chapter, we will be learning more about logical reasoning. Throughout the chapter, we will...

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