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  • Book Overview & Buying Applied Computational Thinking with Python
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Applied Computational Thinking with Python

Applied Computational Thinking with Python - Second Edition

By : Sofía De Jesús, Martinez
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Applied Computational Thinking with Python

Applied Computational Thinking with Python

By: Sofía De Jesús, Martinez

Overview of this book

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.
Table of Contents (25 chapters)
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1
Part 1: An Introduction to Computational Thinking
10
Part 2: Applying Python and Computational Thinking
16
Part 3: Data Processing, Analysis, and Applications Using Computational Thinking and Python

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 allows 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 accidentally introduce bugs or make some code loop infinitely. Understanding the characteristics of a good algorithm allows us to reduce those errors, even if we can’t fully eliminate them from our day-to-day work.

In the next chapter, we will learn more about logical reasoning. Throughout the chapter, we will discuss...

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Applied Computational Thinking with Python
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