A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills

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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. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby.

Use Big O notation, the primary tool for evaluating algorithms, 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. Jay Wengrow brings to this book the key teaching practices he developed as a web development bootcamp founder and educator.

Use these techniques today to make your code faster and more scalable.

• Operating Systems: Principles and Practice
• Algorithms Illuminated: Part 1: The Basics
• Algorithms Illuminated (Part 2): Graph Algorithms and Data Structures (Volume 2)
• Cracking the Coding Interview: 189 Programming Questions and Solutions
• Computer Science Distilled: Learn the Art of Solving Computational Problems
• Once Upon an Algorithm: How Stories Explain Computing (The MIT Press)
• Elements of Programming Interviews in Python: The Insiders' Guide
• Think Like a Programmer: An Introduction to Creative Problem Solving
• Algorithms Illuminated (Part 3): Greedy Algorithms and Dynamic Programming
• Grokking Algorithms: An illustrated guide for programmers and other curious people