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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Identifying errors in algorithm design

Errors in algorithms are just a fact of life for any coder. It's important to get comfortable with making mistakes. As mentioned in Chapter 5, Exploring Problem Analysis, and Chapter 6, Solution Processes and Design, it's good practice to test your algorithm and test it often. Waiting until you have finished hundreds or thousands of lines of code to test something is a recipe for disaster. And yes, I was once working on copying a game and did not test at all. Not until I had all 4,585 lines copied. I was young. Truth be told, I never found the error I made. I started over and started testing at every corner. The second time was successful, but I'd wasted weeks copying everything (it was from a book—GitHub wasn't a thing yet) and then trying to figure out the errors. So please don't be me. Please test your algorithms.

Now, before moving on to debugging and working with codes, let's take a look at the errors...