Data Structures and Algorithms Essentials You Always Wanted to Know

Know about the book -

Data Structures and Algorithms Essentials You Always Wanted to Know is written by Vibrant Publishers and published by Vibrant Publishers. It's available with International Standard Book Number or ISBN identification 1636516335 (ISBN 10) and 9781636516332 (ISBN 13).

· Learn how to write code that doesn’t just work—but works smarter · Understand the performance impact of data structures and algorithm choices · Master essential patterns like recursion, dynamic programming, and greedy logic · Use practical tools to solve real problems with efficient, scalable Python code You’ve mastered the basics of Python— now it’s time to think bigger. It’s time to write code that’s not just correct, but smart, efficient, and built to scale. Data Structures and Algorithms Essentials You Always Wanted to Know helps you transition from Python basics to tackling complex problems with ease. It’s your next step towards mastering the tools, patterns, and thinking needed to tackle real-world challenges—whether you're optimizing performance, preparing for interviews, or building smarter apps. From core concepts like Big O notation, lists, stacks, and queues, to advanced structures like linked lists, trees, and graphs, this book guides you through each topic with crystal-clear explanations and Python-based examples. You'll also explore powerful strategies such as recursion, greedy algorithms, and dynamic programming, learning not just how they work—but when and why to use them. This isn’t a theory-heavy textbook. It’s a practical guide, grounded in application. Each chapter includes hands-on coding tasks, quizzes, case studies, and real-world scenarios—like managing team rosters, analyzing social networks, or checking for palindromes—to help you apply what you learn in meaningful ways. You’ll learn how to: · Think algorithmically and communicate your ideas clearly · Analyze and optimize code using Big O notation · Write recursive functions that are both readable and robust · Use classic data structures and design patterns with confidence