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 discussed problem definition, decomposition, and analysis. We used problems to help us go through the process of identifying problems, decomposing them into the relevant parts and identifying constraints, and analyzing our algorithms. We used flowcharts to help us learn about decision-making when designing algorithms and how to organize ideas.

We learned to test our algorithms often. This provided us with the skills and understanding to identify errors early rather than wait until we had too many lines of code, which made it hard to identify those errors. We used an online store and a guessing game to help us understand some of the functionalities available in Python. Throughout the process, we used Boolean code to verify inputs, we used nested if statements, and we learned about how to use dictionaries in solving the problems presented.

In addition, we got a chance to use a dictionary for an algorithm that used user input and variables. Using the...