An introductory textbook for people who have not programmed before. Covers basic MATLAB programming with emphasis on modeling and simulation of physical systems.

Physical Modeling in MATLAB

Downey, Allen

Computers & Technology

Green Tea Press

Elements of Data Science: Getting Started with Data Science and Python

Programming Languages

Think Python

O'Reilly Media, Inc.

Piensa en Python: cómo pensar como un informático

The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (speciﬁcally computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That’s why this chapter is called, “The way of the program.” On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.

Think Python: An Introduction to Software Design

CreateSpace Independent Publishing Platform

Python 2: For Beginners Only starts the new programmer with the concepts of the basics. What is computer memory? What is a variable? What does it mean to "define a variable"? And gradually moves the student toward proficiency in what may be the most exciting language of the day.

Python 2: For Beginners Only

Kindy, Matthew

Currently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end.
Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned.
<ul>
<li>Learn one concept at a time: tackle complex topics in a series of small steps with examples</li>
<li>Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately</li>
<li>Determine which development techniques work best for you, and practice the important skill of debugging</li>
<li>Learn relationships among input and output, decisions and loops, classes and methods, strings and arrays</li>
<li>Work on exercises involving word games, graphics, puzzles, and playing cards</li>
</ul>

Think Java: How to Think Like a Computer Scientist

Mayfield, Chris

Computer Science

O'Reilly Media

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds.
Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material.
You’ll explore:
<ul>
<li>Periodic signals and their spectrums</li>
<li>Harmonic structure of simple waveforms</li>
<li>Chirps and other sounds whose spectrum changes over time</li>
<li>Noise signals and natural sources of noise</li>
<li>The autocorrelation function for estimating pitch</li>
<li>The discrete cosine transform (DCT) for compression</li>
<li>The Fast Fourier Transform for spectral analysis</li>
<li>Relating operations in time to filters in the frequency domain</li>
<li>Linear time-invariant (LTI) system theory</li>
<li>Amplitude modulation (AM) used in radio</li>
</ul>
Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

Think DSP: Digital Signal Processing in Python

Networking & Cloud Computing

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3.
Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.
<ul>
<li>Start with the basics, including language syntax and semantics</li>
<li>Get a clear definition of each programming concept</li>
<li>Learn about values, variables, statements, functions, and data structures in a logical progression</li>
<li>Discover how to work with files and databases</li>
<li>Understand objects, methods, and object-oriented programming</li>
<li>Use debugging techniques to fix syntax, runtime, and semantic errors</li>
<li>Explore interface design, data structures, and GUI-based programs through case studies</li>
</ul>

Think Python: How to Think Like a Computer Scientist

If you’re a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering—data structures and algorithms—in a way that’s clearer, more concise, and more engaging than other materials.
By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You’ll explore the important classes in the Java collections framework (JCF), how they’re implemented, and how they’re expected to perform. Each chapter presents hands-on exercises supported by test code online.
<ul>
<li>Use data structures such as lists and maps, and understand how they work</li>
<li>Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree</li>
<li>Analyze code to predict how fast it will run and how much memory it will require</li>
<li>Write classes that implement the Map interface, using a hash table and binary search tree</li>
<li>Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results</li>
</ul>
Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.

Think Data Structures: Algorithms and Information Retrieval in Java

Programming

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Books by Downey, Allen