Dealing with Algorithms

Course Curriculum

Chapter 1: Introduction

Lecture 1: What is covered in the course?

Lecture 2: Who and Why you should watch this course?

Chapter 2: Introduction to Algorithms

Lecture 1: Introductory Content

Lecture 2: Why Algorithms?

Lecture 3: Characteristics of an algorithm

Chapter 3: Design and Analysis of Algorithm

Lecture 1: Steps involved in design & analysis of algorithm

Lecture 2: Pseudocode and flowchart

Lecture 3: Solving a problem using different algorithms

Chapter 4: Performance Analysis

Lecture 1: What is Time complexity & Space Complexity ?

Lecture 2: Asymptotic Notations

Lecture 3: Big O notation

Lecture 4: Big Omega and Theta notation

Chapter 5: Time Complexity & Space Complexity

Lecture 1: Types of Time complexities

Lecture 2: Types of time complexities in detail

Lecture 3: Calculating Space Complexity

Lecture 4: Calculating Time Complexity

Chapter 6: Algorithm design techniques & Brute force approach

Lecture 1: Various algorithm design techniques

Lecture 2: Brute force Approach and Example algorithm1: Travelling Salesman Problem

Lecture 3: Exact String Matching Problem using brute force approach

Chapter 7: Divide and conquer design technique

Lecture 1: Introduction to Divide & Conquer approach and Example Algorithm1: Tower of Hanoi

Lecture 2: A variant to Divide and Conquer: Decrease and Conquer

Lecture 3: Decrease and Conquer Approach Algorithm: Binary Search

Lecture 4: Divide and Conquer Technique Example Algorithm 2: Quick Sort

Lecture 5: Master theorem for Divide and Conquer Recurrences

Lecture 6: Divide and Conquer Technique Example Algorithm 3: Merge sort

Lecture 7: Divide and Conquer Technique Example Algorithm 4: Heap sort

Chapter 8: Greedy algorithm technique

Lecture 1: Introduction to greedy algorithm & Greedy algorithm example 1: Huffman Coding

Lecture 2: Greedy algorithm example 2: Kruskal's algorithm part 1

Lecture 3: Kruskal's algorithm part 2 – Union find algorithm and detecting cycle in graph

Lecture 4: Kruskal's algorithm part 3 – Union find algorithm by path compression and rankin

Lecture 5: Greedy Algorithm example 3: Dijkstra's Shortest Path Algorithm

Lecture 6: Greedy Algorithm example 4: Prim's algorithm

Lecture 7: Greedy Algorithm example 4: Fractional knapsack problem

Chapter 9: Dynamic Programming

Lecture 1: Introduction to Dynamic Programming

Lecture 2: Dynamic Programming Example Algorithm 1: Matrix chain multiplication – part 1

Lecture 3: Dynamic Programming Example Algorithm 1: Matrix chain multiplication – part 2

Lecture 4: Dynamic Programming Example Algorithm 1: Matrix chain multiplication – part 3

Lecture 5: Dynamic Programming Example Algorithm 2: Least Common Subsequence – part 1

Lecture 6: Dynamic Programming Example Algorithm 2: Least Common Subsequence – part 2

Lecture 7: Dynamic Programming Example 3: Floyd Warshall Shortest path algorithm – part 1

Lecture 8: Dynamic Programming Example 3: Floyd Warshall Shortest path algorithm – part 2

Lecture 9: Dynamic Programming Example 4: 01 knapsack problem

Lecture 10: Dynamic Programming Example 4: 01 knapsack problem implementation

Lecture 11: Dynamic Programming Example 5: Travelling Salesman Problem

Lecture 12: Dynamic Programming Example 5: Travelling Salesman Problem implementation

Chapter 10: Backtracking design technique

Lecture 1: Introduction to backtracking

Lecture 2: Backtracking algorithm 1 – N Queen problem

Lecture 3: Backtracking algorithm 2 – Graph colouring problem

Lecture 4: Backtracking algorithm 3 – Hamiltonian Cycle

Chapter 11: Branch and Bound design technique

Lecture 1: Introduction to Branch and Bound design technique

Lecture 2: Branch and Bound Algorithm example 1 : 01 knapsack problem

Lecture 3: Branch and Bound Algorithm example 1 : 01 knapsack problem implementation

Lecture 4: Branch and Bound Algorithm example 2: Travelling salesman problem

Lecture 5: Branch and Bound Algorithm example 2: Travelling Salesman problem implementation

Chapter 12: Classification Of Algorithms

Lecture 1: P, NP – NP Hard and NP Complete

Chapter 13: Conclusion

Lecture 1: Congratulations!!!