Book description
Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains
Key Features
 Develop logical reasoning and problemsolving skills that will help you tackle complex problems
 Explore core computer science concepts and important computational thinking elements using practical examples
 Find out how to identify the bestsuited algorithmic solution for your problem
Book Description
Computational thinking helps you to develop logical processing and algorithmic thinking while solving realworld 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.
What you will learn
 Find out how to use decomposition to solve problems through visual representation
 Employ pattern generalization and abstraction to design solutions
 Build analytical skills required to assess algorithmic solutions
 Use computational thinking with Python for statistical analysis
 Understand the input and output needs for designing algorithmic solutions
 Use computational thinking to solve data processing problems
 Identify errors in logical processing to refine your solution design
 Apply computational thinking in various domains, such as cryptography, economics, and machine learning
Who this book is for
This book is for students, developers, and professionals looking to develop problemsolving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.
Publisher resources
Table of contents
 Applied Computational Thinking with Python
 Why subscribe?
 Contributors
 About the authors
 About the reviewer
 Packt is searching for authors like you
 Preface
 Section 1: Introduction to Computational Thinking
 Chapter 1: Fundamentals of Computer Science
 Chapter 2: Elements of Computational Thinking
 Chapter 3: Understanding Algorithms and Algorithmic Thinking
 Chapter 4: Understanding Logical Reasoning
 Chapter 5: Exploring Problem Analysis
 Chapter 6: Designing Solutions and Solution Processes
 Chapter 7: Identifying Challenges within Solutions
 Section 2:Applying Python and Computational Thinking
 Chapter 8: Introduction to Python
 Chapter 9: Understanding Input and Output to Design a Solution Algorithm
 Chapter 10: Control Flow
 Chapter 11: Using Computational Thinking and Python in Simple Challenges
 Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python
 Chapter 12: Using Python in Experimental and Data Analysis Problems
 Chapter 13: Using Classification and Clusters
 Chapter 14: Using Computational Thinking and Python in Statistical Analysis

Chapter 15: Applied Computational Thinking Problems
 Technical requirements
 Problem 1 – Using Python to analyze historical speeches
 Problem 2 – Using Python to write stories
 Problem 3 – Using Python to calculate text readability
 Problem 4 – Using Python to find most efficient route
 Problem 5 – Using Python for cryptography
 Problem 6 – Using Python in cybersecurity
 Problem 7 – Using Python to create a chatbot
 Summary

Chapter 16: Advanced Applied Computational Thinking Problems
 Technical requirements
 Problem 1 – Using Python to create tessellations
 Problem 2 – Using Python in biological data analysis
 Problem 3 – Using Python to analyze data for specific populations
 Problem 4 – Using Python to create models of housing data
 Problem 5 – Using Python to create electric field lines
 Problem 6 – Using Python to analyze genetic data
 Problem 7 – Using Python to analyze stocks
 Problem 8 – Using Python to create a convolutional neural network (CNN)
 Summary
 Other Books You May Enjoy
Product information
 Title: Applied Computational Thinking with Python
 Author(s):
 Release date: November 2020
 Publisher(s): Packt Publishing
 ISBN: 9781839219436
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