Introduction to Data Structures & Algorithms

Course Curriculum

Chapter 1: Introduction

Lecture 1: Pilot

Lecture 2: MinGW for gcc Compiler

Lecture 3: Setting the path for gcc Compiler

Lecture 4: Introduction

Chapter 2: Time Complexity

Lecture 1: Master Method

Lecture 2: Recursion Tree Method

Chapter 3: Sorting Algorithms

Lecture 1: Bubble Sort

Lecture 2: Selection Sort

Lecture 3: Insertion Sort

Lecture 4: Merge Sort

Lecture 5: Quick Sort

Lecture 6: Heap Sort

Lecture 7: Counting Sort

Lecture 8: Radix Sort

Lecture 9: Bucket Sort

Lecture 10: Tree Sort

Chapter 4: Divide & Conquer Algorithms

Lecture 1: Introduction

Lecture 2: Powering a Number

Lecture 3: Fibonacci Series

Lecture 4: Strassen's Algorithm for Matrix Multiplication

Chapter 5: Hashing

Lecture 1: Introduction

Lecture 2: Find all Triplets with 0 Sum

Lecture 3: Smallest element repeated 'k' times in an array

Lecture 4: Duplicate element within 'k' length

Lecture 5: Count Subarrays with equal number of 0's & 1's

Lecture 6: Minimum Deletions to make all the elements of an Array Same

Lecture 7: Group Words with same set of Characters

Lecture 8: Longest Subarray with Sum divisible by 'k'

Chapter 6: Binary Search Tree

Lecture 1: Introduction

Lecture 2: Insertions in a Tree

Lecture 3: Deletions in a Tree

Lecture 4: Traversals Order in a Tree

Lecture 5: Rotations in a Tree

Lecture 6: Red Black Tree – Introduction

Chapter 7: Trie

Lecture 1: Introduction

Lecture 2: Insert & Search in a Trie

Lecture 3: Delete Operations in a Trie

Lecture 4: Sorting Array of Strings using Trie

Lecture 5: Auto Complete Feature using Trie

Lecture 6: How to Implement Reverse DNS LookUp Cache

Lecture 7: How to Implement Forward DNS LookUp Cache

Chapter 8: Priority Queue

Lecture 1: Introduction to Priority Queue

Lecture 2: Priority Queue Implementation (Default)

Lecture 3: Min-Heap for Priority Queue Implementation

Chapter 9: Dynamic Programming

Lecture 1: Introduction

Lecture 2: Memoization

Lecture 3: Longest Common Subsequence

Lecture 4: 0-1 Knapsack Problem

Lecture 5: Fractional Knapsack

Lecture 6: Weighted Job Scheduling

Chapter 10: Graphs

Lecture 1: Introduction

Lecture 2: Graph Representation Methods, Adjacency Matrix

Lecture 3: Graph Representation Methods, Adjacency List

Lecture 4: Minimum Spanning Tree : Kruskal's Algorithm

Lecture 5: Minimum Spanning Tree : Prim's Algorithm

Lecture 6: Detect Cycle in a Directed Graph

Lecture 7: Detect Cycle in an Undirected Graph

Lecture 8: Topological Sorting

Lecture 9: Check whether the given Graph is Bipartite or not

Lecture 10: Breadth First Search(BFS)

Lecture 11: Depth First Search(DFS)

Lecture 12: Single Source Shortest Paths : Dijkstra's Algorithm

Lecture 13: Single Source Shortest Paths : Bellman Ford Algorithm

Lecture 14: All Source Shortest Paths : Floyd Warshall Algorithm

Lecture 15: Detecting Negative Cycle using Floyd Warshall

Chapter 11: Pattern Searching

Lecture 1: Naive Pattern Searching

Lecture 2: KMP Algorithm

Lecture 3: Rabin Karp Algorithm

Lecture 4: Finite Automata Algorithm

Lecture 5: Boyer Moore's Algorithm

Lecture 6: Z Algorithm

Chapter 12: Geometric Algorithms

Lecture 1: Closest Pair of Paths

Lecture 2: How to check if Two Line Segments Intersect

Lecture 3: Convex Hull (Jarvis's Algorithm or Wrapping)

Lecture 4: How to check if Given FOUR Points form a Square

Chapter 13: Mathematical Algorithms

Lecture 1: Multiply TWO Numbers, without using Multiplication, Division or Bitwise Operator

Lecture 2: Babylonian Method of Square Root

Lecture 3: Sieve of Eratosthenes