Algorithms and Data Structure – Data Structures for Everyone!: Discover All You Need To Know!

Length: 65 pages
Edition: 1
Language: English
Publication Date: 2021-10-23
ISBN-10: B09GQYKNZT
ISBN-13: 9798750705092
Sales Rank: #0 (See Top 100 Books)

Do You Want to Know More About Algorithms and Data Structure? Keep reading…

What is Data Structure? What is Linear data Structure? What is Non-Linear Data Structure? What Are Some Applications of Data Structures? What are some Benefits of Learning Data Structures? Can you Tell How Linear Data Structures Differ from Non-Linear Data Structures? What is a Multidimensional Array? What is a Linked List? What are Stacks? What Are the Applications of Stack? What is Array Coding?

So, you want More Information on Algorithms and Data Structures? Keep reading…

“Although greed is considered one of the seven deadly sins, it turns out that greedy algorithms often perform quite well.” Stuart Russell

In this book you will discover What Data Structures and Algorithms are but in an Entirely Fun way!
How Data Structures relate to Java
Fascinating use of Data Structures and Algorithms using Some Amazing Programming Languages, a Must read
This Common-Sense Approach to data Structures and Algorithms

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Introduction
    What Are Data Structures?
    What Is an Algorithm?
    What Are You Going to Learn From This Book?
    Software to Install
Chapter 1: Common Sense Guide to Data Structures and Algorithms
    What Can Be Called a Good Program?
        Characteristics of an Exemplary Algorithm:
    Big O Notation
Chapter 2: Data Structures Using Java
    Arrays in Java
    Stacks in Java
        Stack Overflow
    Queues in Java
Chapter 3: Data Structures Using C++
    Linked Lists
        How to Create a Node?
        Different Types of Linked List
    Binary Trees in C++
    Binary Search Tree
    Recursive Algorithm
Chapter 4: Data Structures in Python
    Lists
    Tuples
    Dictionaries
    Sets
    Different Algorithmic Classes in Python
Chapter 5: Data Structures in Rust
    Red Black Tree
Conclusion
    What Next?
References