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 discussed control flow and order by looking at for loops, range, while loops, and functions. Control flow refers to the order a program reads an algorithm. Typically in Python, one line is read right after the other. In this chapter, we learned how you can control that order. Specifically, we learned that we could do so by iterating through data. Here are some important points to remember: while loops run so long as a condition is met, for loops iterate over a sequence (string, numerical, list, dictionary, set, or tuple), and range is used to create a sequence of numbers.

We also learned that we can combine these things when creating conditions, defining functions, and designing our algorithms. The most important thing to continue keeping in mind is that order matters, so we need to be careful about when we define necessary variables and how to write the algorithms so that they don't run infinitely or break before they should. Control flow is important...