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)
Section 1: Introduction to Computational Thinking
Section 2:Applying Python and Computational Thinking
Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python
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In this chapter, we went over the computational thinking process one more time by working through a more complex scenario and interpretations of that scenario. We learned how to decompose the problem provided, then identify the patterns, generalize them, and design the algorithms. We used some of what we've learned throughout the book to write an algorithm that provided the information we needed.

The computational thinking process helps us develop skills that make our algorithm planning much easier. By walking through that process, we learn more about what Python capabilities and functions may help us in particular scenarios. We also learned how to generalize patterns, sometimes in simple equations for a problem, but other times in creating algorithms that can help us in multiple scenarios without having to recreate them each time. As we got to learn more about Python, we got more comfortable with the computational thinking process in this last chapter of Section 2...