Applied Computational Thinking with Python

Design algorithmic solutions for complex and challenging real-world problems

Sofia De Jesus , Dayrene Martinez 지음

Packt(GCO Science) 2020년 11월 27일 출간

작품소개

책소개

Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains

▶Book Description
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.

▶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 des

목차

▶TABLE of CONTENTS
▷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
-Chapter 16: Advanced Applied Computational Thinking Problems

책 속으로

▶What this book covers
- Chapter 1, Fundamentals of Computer Science, helps you learn about the fundamental elements of computer science, including theory, design, computational processes and systems, and computers. The focus of this chapter will be on the software elements of computer science.

- Chapter 2, Elements of Computational Thinking, explains each of the elements of computational thinking―decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design―and how the process of computational thinking is not linear. Rather, a developer can go back through some of these elements at all stages of the algorithm design process until a solution for a particular problem is reached. This chapter will include some short, relevant problems that are used to demonstrate the use of the elements of computational thinking to arrive at the algorithm.

- Chapter 3, Understanding Algorithms and Algorithmic Thinking, provides you with an introduction to algorithms and their definition. You will also review some algorithms to help you develop the analysis skills necessary when assessing algorithms.

- Chapter 4, Understanding Logical Reasoning, explores logical reasoning processes such as conditional statements, algorithmic reasoning, and Boolean logic. Throughout the chapter, you will learn basic and intermediate logic processing skills through real and relevant problem analysis.

- Chapter 5, Exploring Problem Analysis, explores topics in problem analysis, focusing on problem definition, decomposition, and analysis. In order to practice and further understand the first element of computational thinking, decomposition, you will be presented with real and relevant problems. You will then be able to define and decompose the problem into parts, such as identifying input and output, and additional relevant information needed to begin planning solutions for the problems presented.

- Chapter 6, Designing Solutions and Solution Processes, gives you an

출판사 서평

▶ Preface
Applied Computational Thinking with Python provides a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time. Developers working with Python will be able to put their knowledge to work with this practical guide using the computational thinking method for problem solving.

This book will help 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 practice solving problems in multiple areas, including economics, mathematics, and artificial intelligence.

The 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.

We'll find out how to use decomposition for solving problems through visual representation. We'll also employ pattern generalization and abstraction for designing solutions and building the analytical skills required to assess algorithmic solutions. We'll also use computational thinking with Python for statistical analyses.

We will understand the input and output requirements in terms of designing algorithmic solutions, and use computational thinking to solve data processing problems. We'll identify errors in logical processing to refine your solution design and apply computational thinking in various domains, such as cryptography, economics, and machine learning.

You'll then learn about the various techniques involved in problem analysis, logical reasoning, algorithm design, classification and clusters, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions.

We'll also develop logical reasoning and problem-solving skills that will help you tackle complex problems. We'll also explore core computer science concepts and important computational thinking elements using practical examples and find out how to identify the algorithmic solution that is best-suited to your problem.

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 apply computational thinking techniques to software development.

작가정보

저자(글) Sofia De Jesus

Sofia De Jesus is a computational thinking teacher with a degree from the University of Puerto Rico with a focus on math. She has a master's degree from the University of Dayton. Her experience in education and development spans two decades. She has worked with clients to develop solutions in multiple programming languages. As a teacher, Sofia helps students incorporate the philosophy of computational thinking in courses like game design, circuits, Python, web design, and robotics. She likes to play video games and spend time with her 11 year old Yorkie, King Kong. Sofia also enjoys creating materials, small furniture, and jewelry using CNC machines and laser cutters. She enjoys spending as much time in Puerto Rico as work and life permits.

저자(글) Dayrene Martinez

Dayrene Martinez is a Systems Engineer in the Defense Industry where she develops neural networks embedded in real-time software to aid in decision making for aerospace vehicles. She received a B.S. in Electrical Engineering from the New Jersey Institute of Technology (NJIT). Dayrene is passionate about STEM education and volunteers her free time to inspire the next generation of engineers. She is an active supporter and keynote speaker for the non-profit organization Latinas in STEM. She teaches middle and high school students circuitry, robotics design and software engineering.