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Course Discussion
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Important
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01 - Introduction
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101 - why ds and algo ?
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1.02 - what is data structure
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1.03 - what is an algorithm
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1.04 - Real example of Ds and algorithm
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02 - Big O Notation
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2.01 - solving our first problem
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How you should Proceed?
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2.02 - solving our problem with different approach
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2.03 - the big o notation
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2.04 - comparing both algorithms
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2.05 - cases in big o notation
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2.06 - data structure and time complexity
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2.07 - Cheat sheet of ds and algo
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link
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03 - Problem solving approach
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3.01 - How to solve a problem
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NOTICE
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3.02 - counting frequency solution 1
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3.03 - counting frequency solution 2
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304 - anagram problem
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3.05 - sum zero problem
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3.06 - sum zero problem solution 2
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3.07 - counting unique numbers
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3.08 - longest unique string solution 1
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3.09 - longest unique sum - solution 2
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3.10 - divide and conquerer
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3.11 - instagram ads algorithm problem
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04 - Recursion
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4.01 - what is recursion
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4.02 - call stack
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4.03 - Using Recursive function
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4.04 - advance recursive function
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4.05 - helper recursive function
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05 - Search Algorithms
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5.01 - intro to search algorithms
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5.02 - linear search algorithm
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5.03 - Intro Binary search algorithm
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5.04 - Binary Search Algorithm
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5.05 - Intro to Naive Search Algorithm
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5.06 - Naive search algorithm
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5.07 - Intro to kmp algorithm
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5.08 - Calculating IPS table
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5.09 - Kmp algorithm
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06 - Bubble Sort
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6.01 - introduction to sorting
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6.02 - js built in sort
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6.03 - intro to bubble sort
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6.04 - bubble sort implementation
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6.05 - bubble sort optimisation
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07 - Selection Sort
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7.01 - intro to selection sort
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7.02 - selection sort algorithm
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08 - Insertion Sort
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8.01 - intro to insertion algorithm
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8.02 - insertion sort algorithm
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8.03 - comparing all three algorithms
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09 - Merge Sort
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9.01 - intro to intermediate level algorithms
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9.02 - intro to merge sort
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9.03 - intro to merging
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9.04 - implementing merge logic
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9.05 - merge sort implementation
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9.06 - time complexity of merge sort
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10 - Quick Sort
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10.01 - intro to quick sort
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10.02 - pivot utility
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10.03 - pivot utility implementation
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10.04 - Quick sort implementation
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10.05 - Quick sort explanation
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Time Complexity of Quick Sort
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11 - Radix Sort
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11.01 - intro to radix algorithm
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11.02 - radix helper utility
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11.03 - radix sort
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11.04 - time complexity of radix sort
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12 - Single Linked List Data Structure
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12.01 - into to data structures
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12.02 - linked list introduction
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12.03 - kickstart single linked list
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12.04 -single linked list push
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12.05 - linked list pop possible solution
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12.06 - linked list pop solution
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12.07 - linked list push at head
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12.08 - linked list shift
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12.09 - linked list get
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12.10 - single linked list set
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12.11 - single linked list insert
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12.12 - single linked list remove
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12.13 - single linked list reverse intro
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12.14 - single linked list reverse
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12.15 - single linked list time complexity
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13 - Tree Traversal
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13.01 - doubly linked list intro
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13.02 - doubly linked list setup
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13.03 - Doubly linked list push
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13.04 - dll pop
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13.05 - dll shift
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13.06 - dll unshift
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13.07 - dll get
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13.08 - dll set
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13.09 - dll insert
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13.10 - dll remove
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13.11 - sll vs dll
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14 - Stacks & Queues
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14.01 - intro to stack
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14.02 - array as stack
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14.03 - creating a stack from scratch
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14.04 - time complexity of stack
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14.05 - intro to queue
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14.06 - using queue from array
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14.07 - creating queue from scratch
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14.08 - time complexity of queue
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15 - Binary Search Trees
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15.01 - intro to trees
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15.02 - Uses of Trees
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15.03 - intro to binary tree
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15.04 - searching in bst
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15.05 - BST setup
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15.06 - Bst Insert
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15.07 - BST find
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16 - Tree Traversal
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16.01 - intro to tree traversal
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16.02 - BFS
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16.03 - DFS pre order
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16.04 - Dfs pre order
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16.05 - Dfs post order
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16.06 - Dfs post order solution
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16.07 - dfs in order
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16.08 - dfs in order solution
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16.09 - Dfs vs Bfs
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17 - Binary Heap
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17.01 - intro to binary heaps
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17.02 -Sorting heaps
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17.03 - intro to binary heap insert
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17.04 - max heap insert solution
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17.05 - max heap extract max intro
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17.06 - heap extract max solution
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17.07 - priority queue intro
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17.08 - priority queue part 1
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17.09 - priority queue part 2
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17.10 - time complexity of binary heap
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18 - Hash Tables
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18.01 - intro to hash tables
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18.02 - intro to hash functions
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18.03- writing our own hash functions
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18.04 - improving our hash function
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18.05 - handling collision
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18.06 - hash table set and get
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18.07 - hash table set solution
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18.08 - hash table get solution
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18.09 - Hash table key and value
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18.10 - Time complexity of hash tables
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19 - Graphs
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19.01 - Intro to Graphs
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19.02 - use cases of graphs
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19.03 - types of graph
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19.04 - adjacency matrix & adjacency list
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19.05 - time complexity of adjacency matrix vs adjacency list
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19.06 - Add vertex
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19.07 - add edge
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19.08 - remove edge
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19.09 - remove vertex
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20 - Graph Traversal
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20.01 - intro to graph traversal
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20.02 - Intro to Graph Dfs
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20.03 - graph dfs recursively
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20.04 - graph dfs recursively explaination
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20.05 - graph dfs iteratively
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20.06 - bfs intro
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20.07 - bfs solution
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21 - DIJKSTRA’S Algorithm
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21.01 - Dijkstra's algorithm
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21.02 - creating weighted graph
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21.03 - Dijkstra's walkthrough
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21.04 - Dijkstra's implementation
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21.05 - optimisation of algorithm
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Conclusion
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js data structure and algorithm
Preview - Data structures and algorithms (JS)
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