The Self-Taught Computer Scientist
The Self-Taught Computer Scientist

Author: Cory Althoff

Publisher: John Wiley & Sons

Published: 2021-09-16

Total Pages: 336

ISBN-13: 1119724333

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The follow-up to Cory Althoff's bestselling The Self-Taught Programmer, which inspired hundreds of thousands of professionals to learn to program outside of school! Fresh out of college and with just a year of self-study behind him, Cory Althoff was offered a dream first job as a software engineer for a well-known tech company, but he quickly found himself overwhelmed by the amount of things he needed to know, but hadn’t learned yet. This experience combined with his personal journey learning to program inspired his widely praised guide, The Self-Taught Programmer. Now Cory's back with another guide for the self-taught community of learners focusing on the foundations of computer science. The Self-Taught Computer Scientist introduces beginner and self-taught programmers to computer science fundamentals that are essential for success in programming and software engineering fields. Computer science is a massive subject that could cover an entire lifetime of learning. This book does not aim to cover everything you would learn about if you went to school to get a computer science degree. Instead, Cory's goal is to give you an introduction to some of the most important concepts in computer science that apply to a programming career. With a focus on data structures and algorithms, The Self-Taught Computer Scientist helps you fill gaps in your knowledge, prepare for a technical interview, feel knowledgeable and confident on the job, and ultimately, become a better programmer. Learn different algorithms including linear and binary search and test your knowledge with feedback loops Understand what a data structure is and study arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs Prepare for technical interviews and feel comfortable working with more experienced colleagues Discover additional resources and tools to expand your skillset and continue your learning journey It's as simple as this: You have to study computer science if you want to become a successful programmer, and if you don't understand computer science, you won't get hired. Ready for a career in programming, coding, or software engineering and willing to embrace an "always be learning" mindset? The Self-Taught Computer Scientist is for you.

A Programmer's Guide to Computer Science
A Programmer's Guide to Computer Science

Author: William M Springer II

Publisher:

Published: 2020-01-03

Total Pages: 188

ISBN-13: 9781951204037

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You know how to code..but is it enough? Do you feel left out when other programmers talk about asymptotic bounds? Have you failed a job interview because you don't know computer science? The author, a senior developer at a major software company with a PhD in computer science, takes you through what you would have learned while earning a four-year computer science degree. Volume one covers the most frequently referenced topics, including algorithms and data structures, graphs, problem-solving techniques, and complexity theory. When you finish this book, you'll have the tools you need to hold your own with people who have - or expect you to have - a computer science degree.

Computer Science Distilled
Computer Science Distilled

Author: Wladston Ferreira Filho

Publisher: Code Energy

Published: 2017-01-17

Total Pages: 188

ISBN-13: 0997316012

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A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work.

A Common-Sense Guide to Data Structures and Algorithms, Second Edition
A Common-Sense Guide to Data Structures and Algorithms, Second Edition

Author: Jay Wengrow

Publisher: Pragmatic Bookshelf

Published: 2020-08-10

Total Pages: 714

ISBN-13: 1680508059

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Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today’s web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code, with examples in JavaScript, Python, and Ruby. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You’ll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your code faster and more scalable.

Street Coder
Street Coder

Author: Sedat Kapanoglu

Publisher: Simon and Schuster

Published: 2022-02-08

Total Pages: 270

ISBN-13: 1617298379

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This wickedly smart and devilishly funny beginner's guide shows you how to get the job done by prioritizing tasks, making quick decisions, and knowing which rules to break. --

Introduction to Algorithms, third edition
Introduction to Algorithms, third edition

Author: Thomas H. Cormen

Publisher: MIT Press

Published: 2009-07-31

Total Pages: 1313

ISBN-13: 0262258102

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The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.

HT THINK LIKE A COMPUTER SCIEN
HT THINK LIKE A COMPUTER SCIEN

Author: Jeffrey Elkner

Publisher: Samurai Media Limited

Published: 2016-10-04

Total Pages: 306

ISBN-13: 9789888406784

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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.

Algorithms, Part II
Algorithms, Part II

Author: Robert Sedgewick

Publisher: Addison-Wesley Professional

Published: 2014-02-01

Total Pages: 973

ISBN-13: 0133847268

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This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

How Computers Really Work
How Computers Really Work

Author: Matthew Justice

Publisher: No Starch Press

Published: 2020-12-29

Total Pages: 394

ISBN-13: 171850067X

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An approachable, hands-on guide to understanding how computers work, from low-level circuits to high-level code. How Computers Really Work is a hands-on guide to the computing ecosystem: everything from circuits to memory and clock signals, machine code, programming languages, operating systems, and the internet. But you won't just read about these concepts, you'll test your knowledge with exercises, and practice what you learn with 41 optional hands-on projects. Build digital circuits, craft a guessing game, convert decimal numbers to binary, examine virtual memory usage, run your own web server, and more. Explore concepts like how to: Think like a software engineer as you use data to describe a real world concept Use Ohm's and Kirchhoff's laws to analyze an electrical circuit Think like a computer as you practice binary addition and execute a program in your mind, step-by-step The book's projects will have you translate your learning into action, as you: Learn how to use a multimeter to measure resistance, current, and voltage Build a half adder to see how logical operations in hardware can be combined to perform useful functions Write a program in assembly language, then examine the resulting machine code Learn to use a debugger, disassemble code, and hack a program to change its behavior without changing the source code Use a port scanner to see which internet ports your computer has open Run your own server and get a solid crash course on how the web works And since a picture is worth a thousand bytes, chapters are filled with detailed diagrams and illustrations to help clarify technical complexities. Requirements: The projects require a variety of hardware - electronics projects need a breadboard, power supply, and various circuit components; software projects are performed on a Raspberry Pi. Appendix B contains a complete list. Even if you skip the projects, the book's major concepts are clearly presented in the main text.