Introduction

Before You Start

Introduction to Trees

Understanding Binary & Binary Search Tree

Building Binary Search Tree from scratch!

Travelling Nodes using Recursion

Find Element in Tree

Tree Traversals - Dept First VS Breadth First

Pre-Order Tree Traversal

In-Order Tree Traversal

Post-Order Tree Traversal

Depth and Height of Node

Minimum Value In Tree

Equality Checking

Validating Binary Tree

Nodes at K Distance

Level Order Traversal

Diameter of Tree

Balanced Tree or Not

Sum Tree or Not

Zig Zag Traversal

Boundary Traversal

Vertical Order Traversal

Top View

Bottom View

Right View

Diagonal Traversal

Sum of nodes on the longest path from root to leaf node

 LCA of Binary Tree

Minimum Time To Burn Binary Tree

Morris Traversal

Flatten Binary Tree

Inorder Predecessor/Successor

Kth Smallest/Largest in BST

LCA in BST

Normal BST to Balanced BST

Merge two Binary Trees

Largest BST in Binary Tree

Understanding Rotations

LeftRight and RightLeft Rotation

Creating an AVL Tree from Scratch

Detecting Imbalanced Node

Detecting Rotations - 1

Detecting Rotations - 2 

Implementing Left And Right Rotations

Heap Insert Logic

Creating Heap From Scratch

Removing Element Logic

Heapify

K-th Smallest Element

Check If Binary Tree is a Valid Max Heap

Smallest Range in K lists

Notes

Introduction to TRIE

Building TRIE from Scratch

Auto-Complete using TRIE

Remove Elements From Trie

Longest Common Prefix

Trie Notes

Introduction to Graphs

Adjacency Matrix and Adjacency List 

Building Graph from Scratch

Traversal - Breadth First Search (BFS)

Traversal - Dept First Search (DFS)

Cyclic Detection in Graph

Topological Sort

Kahn's Algorithm

Refactoring Graphs to OOPS Style

Building Directed Weighted Graph

Shortest Path Algorithm

Shortest path Algorithm - Code

Introduction Undirected Graph

Cyclic Detection in Undirected Graphs

Dijkstra's Algorithm - Shortest Path Algorithm

Implementing Dijkstra's Algorithm - Shortest Path Algorithm

Minimum Spanning Tree

Prim's Algorithm

Prim's Algorithm Code

Complete Guide and Hands-on Tutorials on Non-Linear Data Structures

anushka singh

Hi, I am Piyush and I love to explore new technologies and frameworks. I work as a freelancer in various domains such as the Backend engineer, AWS Cloud solution architect, etc. 

Fun fact about me: 
I am obsessed with clean codes that follow proper design principles and patterns.

Piyush Garg

In this online course "Master Non-Linear Data Structures", you will be introduced to the powerful and versatile world of non-linear data structures. These data structures are essential for solving complex problems in computer science, and are used in various fields such as software development, databases, and artificial intelligence. 

You will start by learning about Trees, a basic yet powerful data structure that is used to organize and manage data in a hierarchical structure. You will learn about the different types of Trees, including Binary Search Trees (BST), Binary Trees (BT), and AVL Trees, and how to implement them in code. You will also learn about the various operations that can be performed on Trees, such as insertion, deletion, and search. 

Next, you will dive into Heaps, a data structure that allows for efficient access and manipulation of the largest or smallest element. You will learn about the different types of Heaps, such as max-heaps and min-heaps, and how to implement them in code. 

You will also learn about Tries, a data structure that is used to efficiently store and search large sets of strings. This data structure is particularly useful in applications such as spell-checking and auto-complete. 

Finally, you will delve into Graphs, a data structure that is used to represent relationships between different objects. You will learn about the different types of Graphs, such as undirected and directed graphs, and how to implement them in code. You will also learn about the various algorithms used to traverse and search Graphs, such as depth-first search and breadth-first search. 

Throughout the course, you will be solving many challenging coding questions online to solidify your understanding of these complex data structures. The course is designed for experienced programmers who are looking to expand their knowledge and skills. By the end of the course, you will be a master of non-linear data structures and be equipped to tackle even the most complex coding challenges.

Introduction to Data Structures and Algorithms

Master Linear Data Structures

Complete Java Mastery Course

Master Non-Linear Data Structures

aditya

Anirban

I really understood the way u teach these data structures and it really build my foundation in problem solving. Thank you so much Sir

Komal Maurya

Aman

Sri Anjaneyulu Chegondi

Certificate Details

Master Non-Linear Data Structures

Course Goals

Piyush Garg