Deep Dive into Algorithms

Course Curriculum

Chapter 1: Backtracking

Lecture 1: Introduction

Lecture 2: Concept of N Queen Problem

Lecture 3: Implementation of N Queen Problem

Lecture 4: Time Complexity Analysis of N Queen Problem

Lecture 5: Concept of Knight's Tour Problem

Lecture 6: Implementation of Knight's Tour Problem

Lecture 7: Time Complexity Analysis of Knight's Tour Problem

Lecture 8: Concept Explanation of Rat in a Maze Problem

Lecture 9: Implementation of Rat in a Maze

Lecture 10: Time Complexity Analysis of Rat in a Maze

Lecture 11: Concept Explanation of Subset Sum

Lecture 12: Implementation of Subset Sum Problem

Lecture 13: Time and Space Complexity Analysis of Subset Sum Problem

Lecture 14: Concept Explanation of M-Coloring Problem

Lecture 15: Implementation of M Coloring Problem

Lecture 16: Time and Space Complexity Analysis of M Coloring Problem

Lecture 17: Concept Explanation of Hamiltonian Cycle Problem

Lecture 18: Implementation of Hamiltonian Cycle

Lecture 19: Time and Space Complexity Analysis of Hamiltonian Cycle

Lecture 20: Concept Explanation of Sudoku Solver

Lecture 21: Implementation of Sudoku Solver

Lecture 22: Time and Space Complexity Analysis of Sudoku Solver

Lecture 23: Sieve of Eratosthene

Lecture 24: Implementation of Sieve of Eratosthene

Lecture 25: Concept Explanation of Sieve of Sundaram

Lecture 26: Implementation of Sieve of Sundaram

Lecture 27: Time and Space Complexity Analysis of Sieve of Eratosthene and Sieve of Sundaram

Lecture 28: Sieve of Eratosthene in O(N) Time Complexity

Lecture 29: Implementation of Sieve of Eratosthene in O(N) Time Complexity

Lecture 30: Prime Numbers after P with Sum S

Lecture 31: Implementation of Prime Numbers after P with Sum S

Lecture 32: Time and Space Complexity Analysis of Prime Numbers after P with Sum S

Chapter 2: Dynamic Programming

Lecture 1: Introduction to Dynamic Programming – Part 1

Lecture 2: Introduction to Dynamic Programming – Part 2

Lecture 3: 0/1 Kanpsack Problem

Lecture 4: Implementation of 0/1 Knapsack Problem

Lecture 5: Printing items in 0/1 Knapsack Problem

Lecture 6: Implementation of printing items in 0/1 Knapsack Problem

Lecture 7: Minimum Cost Path

Lecture 8: Implementation of Minimum Cost Path

Lecture 9: Tracing the path of Minimum Cost Path

Lecture 10: Implementation of Tracing the Path of Minimum Cost Path

Lecture 11: Subset Sum Problem

Lecture 12: Implementation of Subset Sum Problem

Lecture 13: Printing items in Subset Sum Problem

Lecture 14: Implementation of printing items in Subset Sum

Lecture 15: Maximum Size Square Sub Matrix with all 1s

Lecture 16: Implementation of Maximum Size Square Sub Matrix with all 1s

Lecture 17: Longest Increasing Subsequence

Lecture 18: Implementation of Longest Increasing Subsequence

Lecture 19: Printing items in Longest Increasing Subsequence

Lecture 20: Implementation of Printing items in Longest Increasing Subsequence

Lecture 21: Longest Common Subsequence

Lecture 22: Implementation of Longest Common Subsequence

Lecture 23: Tracing the String in Longest Common Subsequence

Lecture 24: Implementation of Tracing the String in Longest Common Subsequence

Chapter 3: Range Query Algorithms

Lecture 1: Introduction and Brute Force Approach of Range Minimum Query

Lecture 2: Implementation of Range Minimum Query ( Brute Force Approach )

Lecture 3: Dynamic Programming Approach for Range Minimum Query

Lecture 4: Implementation of Range Minimum Query ( Dynamic Programming Approach )

Lecture 5: Introduction to Segment Tree

Lecture 6: Constructing Segment Tree

Lecture 7: Implementation of Constructing Segment Tree

Lecture 8: Range Minimum Query on the Constructed Segment Tree

Lecture 9: Implementation of Range Minimum Query on Constructed Segment Tree

Lecture 10: Range Minimum Query Using Sparse Table

Lecture 11: Performing RMQ on Constructed Sparse Table

Lecture 12: How to efficiently fill Sparse Table ?

Lecture 13: Implementation of RMQ using Sparse Table

Chapter 4: Graph Algorithms

Lecture 1: How to represent a adjacency list for an directed and undirected graph ?

Lecture 2: Implementation of Adjacency List for Directed and Undirected Graph

Lecture 3: HierHolzer's Algorithm

Lecture 4: Implementation of HierHolzer's Algorithm

Lecture 5: Union Find Algorithm

Lecture 6: Implementation of Union Find Algorithm

Lecture 7: Topological Sorting

Lecture 8: Dijkstra's Algorithm

Lecture 9: Bellman Ford Algorithm

Lecture 10: Ford Fulkerson Method Edmond Karg Maximum Flow Algorithm

Lecture 11: Kargers Algorithm for Minimum Cut

Lecture 12: Kruskal's Algorithm for Minimum Spanning Tree

Lecture 13: Prim's Algorithm for Minimum Spanning Tree