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Applied Computational Thinking with Python

Applied Computational Thinking with Python

By : Sofía De Jesús, Dayrene Martinez
4.6 (11)
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Applied Computational Thinking with Python

Applied Computational Thinking with Python

4.6 (11)
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)
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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 9: Understanding Input and Output to Design a Solution Algorithm

In this chapter, we will take a deeper look at problems in order to identify the input and output necessary to design an algorithm for the problems. We will use concepts we learned in Chapter 8, Introduction to Python, where we discussed object-oriented programming, dictionaries, lists, and more. As you practice getting input and using it in your algorithm, you'll be able to see that the output of an algorithm is dependent on the input information.

In this chapter, we will cover the following topics:

  • Defining input and output
  • Understanding input and output in computational thinking

In this chapter, we will focus on understanding different types of input and how output is used in programming using the Python programming language. To be able to get a better understanding of these topics, we have to first look at their definitions.

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Applied Computational Thinking with Python
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