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