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 inductive and deductive reasoning, logical reasoning, logical operators, and Boolean logic. As we discussed, most of the algorithm designs fall under deductive reasoning. We learned how to use statements, such as if, if-else, if-elif-else, and nested statements, to write programs that test conditions.

In addition, we learned that some errors are difficult to identify, so it is important to verify our programs and test them often.

After going through this chapter, you are now better equipped to write algorithms using logical reasoning. You also have the understanding to apply inductive and deductive reasoning when designing and planning algorithms and use Boolean logic and operators in your algorithms. You are now also able to test your algorithms for errors by identifying possible mistakes such as indentation errors, conditional errors, and formula errors.

In the next chapter, we will be taking a deeper dive deeper into problem analysis...