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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Chapter 7: Identifying Challenges within Solutions

In this chapter, we will be evaluating algorithms and diagrams as we learn to navigate through some common errors and to determine whether possible adjustments can be made to an existing algorithm to simplify it. We will evaluate the solutions based on the problem description to verify whether the solution aligns with the problem. We will be learning about identifying pitfalls in the solution design process. As a note, we will expand on the content of this chapter, later in this book, in Section 2, Applying Python and Computational Thinking, and Section 3, Data Processing, Analysis, and Applications Using Computational Thinking and Python, of this book as we dive deeper into the Python programming language.

To learn about debugging, let's remind ourselves that the computational thinking process is not linear. Even when we are working from the original problem, we will sometimes redefine the problem or need to adjust the generalization...