Book Image

Applied Computational Thinking with Python

By : Sofía De Jesús, Dayrene Martinez
Book Image

Applied Computational Thinking with Python

By: Sofía De Jesús, Dayrene 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 (21 chapters)
1
Section 1: Introduction to Computational Thinking
9
Section 2:Applying Python and Computational Thinking
14
Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python
20
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Summary

In this chapter, we have gone through the computational thinking process. We learned about the four major elements of computational thinking: decomposition, pattern recognition, pattern generalization, and algorithm design. We also learned that problems in computational thinking are not always clearly defined. It is up to us to interpret and decompose the information so we can find the patterns. Once we find the patterns and define what we'd like to generalize, we can then design algorithms in order to solve our problems.

We also learned that algorithms and solutions are not unique. There are multiple ways to write an algorithm for each problem we encounter. The computational thinking process allows us to explore problems in multiple ways and create solutions that align with our own interpretations and needs.

In the next chapter, we will be learning about algorithms and algorithmic thinking more in depth, as they are the product of all computational thinking problems...