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A paperback book titled "Data Structures and Algorithms Essentials" by Shawn Peters .
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know

Data Structures and Algorithms Essentials You Always Wanted to Know

Master Python, Recursion, Dynamic Programming, and Greedy Algorithms With Hands-On Examples

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Description

Learn the core data structures and algorithms for optimized Python coding.

  • 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
Bibliographic Details

Pages: 334 pages

Paperback (ISBN): 9781636516325

Trim Size: 5.5” x 8.5”

Category: Business & Economics

Author: Shawn Peters, Vibrant Publishers

Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Data Structures and Algorithms Essentials You Always Wanted to Know
Table of Contents

Chapter 1 - Introduction to Data Structures and Algorithms

1.1 - What are Data Structures?
1.2 - What Are Algorithms?
1.3 - Importance and Applications
Chapter Summary
Quiz

Chapter 2 - Complexity and Big O Notation

2.1 Analyzing Complexity
2.2 Big O, Omega, and Theta Notation: Worst, Best, and Average Cases
2.3 Trade-offs Between Recursion and Iteration
Chapter Summary
Quiz

Chapter 3 - Arrays

3.1 Introduction to Arrays
3.2 Array Operations
3.3 Array-Based Algorithms
3.4 Practical Application – Team Roster
Chapter Summary
Quiz

Chapter 4 - Stacks and Queues

4.1 Introduction to Stacks
4.2 Introduction to Queues
4.3 Using deque for Stacks and Queues
4.4 Stack and Queue-Based Algorithms
4.5 Practical Applications – Browser History and Print Queues
Chapter Summary
Quiz

Chapter 5 - Linked Lists

5.1 Introduction to Linked Lists
5.2 Types of Linked Lists
5.3 Linked List Operations
5.4 Linked List-Based Algorithms
5.5 Practical Application - Palindrome Checking
Chapter Summary
Quiz

Chapter 6 - Hash Tables

6.1 Introduction to Hashing
6.2 Probing Methods and Hash Functions
6.3 Implementing Hash Tables
6.4 Hash Table Based Algorithms
6.5 Practical Application - Caching
Chapter Summary
Quiz

Chapter 7 - Trees

7.1 Introduction to Trees
7.2 Binary Trees
7.3 - Binary Search Trees (BSTs)
7.4 - Tree-Based Algorithms
7.5 - Practical Application - File Systems
Chapter Summary
Quiz

Chapter 8 - Graphs

8.1 - Introduction to Graphs
8.2 - Types of Graphs
8.3 - Implementing Graphs
8.4 - Graph Based Algorithms
8.5 - Practical Application - Longest Influence Chain
Chapter Summary
Quiz

Chapter 9 - Dynamic Programming and Greedy Algorithms
9.1 Introduction to Dynamic Programming and Greedy Algorithms
9.2 - Greedy Algorithm Examples
9.3 - Memoization vs Tabulation in Dynamic Programming
9.4 - Dynamic Programming Examples
9.5 - Practical Application - Longest Influence Chain Revisited
Chapter Summary
Quiz

Case Studies and Real-World Problems
Case Study 1- Managing a Music Library

Bibliography
Glossary

Author

Shawn Peters has 19 years of teaching experience, is certified in Python Programming Teaching from the College of the North Atlantic, and also specializes in JavaScript and Java.

Vibrant Publishers is focused on presenting the best texts for learning about technology and business as well as books for test preparation. Categories include programming, operating systems and other texts focused on IT. In addition, a series of books helps professionals in their own disciplines learn the business skills needed in their professional growth.

Vibrant Publishers has a standardized test preparation series covering the GMAT, GRE and SAT, providing ample study and practice material in a simple and well organized format, helping students get closer to their dream universities.

Series

The Self-Learning Management Series is designed to help students, new managers, career switchers, and entrepreneurs learn essential management lessons and covers every aspect of business, from HR to Finance to Marketing to Operations across any and every industry. Each book includes basic fundamentals, important concepts, and standard and well-known principles as well as practical ways of application of the subject matter.

Editorial Reviews

An excellent guide for learning the basics of data structures and algorithms with simple explanations and useful examples.
-- Pintu Kumar
Research Scholar,
IEOR, IIT Bombay

Packed with clear explanations of essential DSA concepts, this book is a must-have for anyone serious about mastering data structures and algorithms in Python.
-- Karthik Chandrakant
AI Leader; Head of Data Science & AI at Imarticus Learning; Ex-Amazon, Mu Sigma; TEDx Speaker, Author

Data Structures and Algorithms Essentials You Always Wanted to Know provides a clear, structured, and beginner-friendly introduction to core data structures and algorithms using Python. Each chapter balances theory, practical applications, and quizzes that reinforce learning, making it ideal for self-learners and early computer science and data science students. The inclusion of real-world examples, such as caching and file systems, helps bridge the gap between abstract concepts and hands-on coding. Since I opened the book, I couldn't close it. If you want to learn data structures concepts, this is the learning material for you.
-- Dr. Lawrence Decamora
Computer Science Instructor,
University of Santo Thomas

The book delivers a strong educational experience characterized by clarity, accuracy, and pedagogical effectiveness. It excels at introducing foundational computer science concepts to beginners while maintaining practical relevance through real world coding examples.
-- Aldo Baca
Senior Machine Learning Scientist

Shawn Peters’ book does a great job of explaining how data structures and algorithms are used with real life examples, making complex ideas easy to grasp. I especially loved the way he uses pie baking as a fun illustration—it turns a tricky concept into something clear and relatable. The language is simple, avoiding jargon, and the illustrations really help make the ideas stick. It’s inspiring to see how these skills can be applied in professional settings, linking everyday understanding to real-world problem-solving. Overall, it’s an engaging and practical read that makes learning data structure and algorithms both accessible and relevant to everyday and professional life.
-- Loo Yee NG
Solutions Architect, CTMG

Shawn Peters has created an excellent guide for anyone studying computer science or data science, whether at school, university, or learning independently. This book offers a comprehensive and accessible introduction to essential topics like data structures, arrays, Big O notation, stacks, queues, linked lists, hash tables, trees, graphs, and dynamic programming. With clear explanations, practical Python and pseudocode examples, and real-world applications, it’s a valuable resource for learners preparing for exams, interviews, or building a strong foundation in coding. A smart, well-structured read for students and aspiring developers alike.
-- Jonathan Gillespie
Computer Science & Business Teach

Supplemental Resources

Online Resources

Instructor Resources

Frequently Asked Questions

Everything you need to know before you buy this combo

Basic Python knowledge can be helpful, as the book uses Python-based examples to explain key concepts. However, the accompanying online resources also include downloadable code samples in Java, C++, and JavaScript, making the material useful for learners familiar with other programming languages as well.
Yes. It introduces DSA concepts step by step, starting with the fundamentals before progressing to topics such as trees, graphs, recursion, and dynamic programming.
Yes. You’ll learn Big O, Omega, and Theta notation and how to evaluate the efficiency and performance of algorithms.
Yes. The book helps build skills in algorithmic thinking, data structures, Big O analysis, and problem-solving, all of which are useful when preparing for technical and coding interviews.
Yes. The book includes supplementary online resources such as real-world case studies, coding tasks, and downloadable code samples. The code samples are available in Python, Java, C++, and JavaScript, so you can practice key concepts in the language you are most comfortable with.
It is ideal for beginners with basic programming knowledge, students, aspiring developers, and professionals who want to build stronger problem-solving and algorithmic thinking skills.

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  • 5 stars: 105 (67%)
  • 4 stars: 52 (33%)
  • 3 stars: 0 (0%)
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A
Anonymous

Excellent

L
Le Quang Vinh (Vietnam)
The DSA book I wish I had started with

This took me from knowing Python to actually thinking about efficiency and scale. The structured path through core structures and algorithms, backed by real examples like file systems, made everything stick. I finished ready to tackle real projects and interviews.

T
Tran Minh Khang (Vietnam)
The DSA book I wish I had started with

This took me from knowing Python to actually thinking about efficiency and scale. The structured path through core structures and algorithms, backed by real examples like file systems, made everything stick. I finished ready for real projects and interviews.

V
Vu Minh Tri (Vietnam)
Improved My Algorithmic Problem-Solving Speed

Working through this guide gave me a structured mental model for selecting the right data structure for specific software performance bottlenecks.

A
Aditya Sengupta (India)
Perfect Resource for Self-Paced Computer Science Learning

If you want to master fundamental algorithms and data structures without getting lost in dense textbook prose, this handbook is the perfect entry point.

E
Elvin Mammadov (Azerbaijan)
Essential Reference for Self-Taught Programmers and CS Students

Covers dynamic programming, hash tables, heaps, and binary search trees with clean diagrams without overwhelming the reader with convoluted mathematical jargon.

B
Bui Minh Tri (Vietnam)
Top Recommended Guide for Data Structures

An exceptional compilation. The practical breakdown of searching, sorting, and graph traversals makes this a mandatory handbook for every programmer's library.

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Nualjan Sirikul (Thailand)
Clear and well paced for beginners

As a non native English reader, I found the writing easy to follow and the Python examples very helpful. Working through stacks, queues, and trees with real scenarios built my confidence. A few more advanced graph examples would have been a nice bonus.

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Clear and well paced for beginners

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W
Worawat Srisuk (Thailand)
Structured and Highly Informative Technical Desk Reference

Every chapter concludes with helpful review questions and key takeaway summaries that reinforce time-complexity analysis and algorithmic tradeoffs.

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Top Recommended Guide for Data Structures and Algorithms Mastery

An outstanding handbook. The comprehensive coverage of data organization and algorithm optimization makes this an absolute must-have desk reference.

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Well Written with Clear Visual Memory Diagrams and Code Outlines

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Clear and Intuitive Foundation for Core Computer Science Concepts

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Solid Breakdown of Sorting Algorithms and Memory Efficiency

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Perfect Refresher for Experienced Developers

Even with years of development experience, going back to foundational algorithm concepts is crucial. This book acts as a clean, concise refresher on graph algorithms and searching techniques.

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Pham Minh Tuan (Vietnam)
Boosted My Problem-Solving Speed on Algorithmic Challenges

Working through this guide gave me a structured mental framework for choosing the right data structure for specific software design bottlenecks.

A
Ananda Phung (Thailand)
Structured and Highly Informative Technical Desk Reference

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L
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A
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The step-by-step breakdowns of time and space complexity, Big O notation, and recursive algorithm design make preparing for technical interviews straightforward and stress-free.

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I had tried other algorithm books and given up, but this one kept me reading with its clear, practical style. Learning to analyze code with Big O and apply greedy and dynamic programming strategies felt achievable here. A great resource for self learners like me.

N
Nihad Bagirov (Azerbaijan)
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Masterclass in DSA Fundamentals

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An outstanding handbook. The complete coverage of data organization and algorithm optimization makes this an absolute must-have reference for developers.

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Great Primer for Software Engineers Transitioning to Backend Roles

A very well-structured book. It offers straightforward guidance on graph traversal algorithms like BFS and DFS, algorithm efficiency, and spatial memory management.

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Essential Guide for Self-Taught Programmers and Computer Science Students

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