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  • Book Overview & Buying Applied Computational Thinking with Python
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Applied Computational Thinking with Python

Applied Computational Thinking with Python - Second Edition

By : Sofía De Jesús, Martinez
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Applied Computational Thinking with Python

Applied Computational Thinking with Python

By: Sofía De Jesús, 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 (25 chapters)
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1
Part 1: An Introduction to Computational Thinking
10
Part 2: Applying Python and Computational Thinking
16
Part 3: Data Processing, Analysis, and Applications Using Computational Thinking and Python

Understanding errors

We had previously discussed errors generally; here, we will also include some additional discussions as we progress through the additional content within this book. But at this time, it will be helpful to go over a few more error examples, in particular, errors pertaining to the following:

  • Syntax errors: these are created by misspelling, missing punctuation, and so on.
  • Errors in logic: these are created when the code runs “correctly” but the results do not match our expectations.
  • Type Errors: these are created when we try to use a value with one type, like a string, but the expected value was an int or float and vice versa

Let’s take a look at Syntax Errors first, but then we’ll dedicate a larger section to errors in logic. And we’ll conclude with a discussion on debugging.

Syntax errors

These can be fairly easy to identify, and Python provides us with some console messages to help us. Let’...

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Applied Computational Thinking with Python
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