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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Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python

Data is all around us. We use data to inform decisions about policies, such as how many resources are provided for a school district, how large the budget for a county or state's Medicare program will be, how much we pay for housing in an area, and the trends of the real estate market. Data is embedded in the way that we interact with advertisements too. Simply put, understanding more about data and how to use Python to analyze this data is a really important skillset.

In this section, you will be introduced to advanced functionalities of the Python programming language associated with data analysis and other applications, such as cryptography, experimental data, data mining, and machine learning. We will use computational thinking to design solutions and algorithms for many real-world, applied problems, from those in language and historical analysis to some machine learning...