Algorithms

by Abdul Bari · 84 videos

Listed in Best free DSA courses on YouTube, ranked by total hours

Total watch time

1d 4m

at speed · exactly 1 day, 3 minutes, 46 seconds at 1×

1d 3m 46s
1.25×19h 15m 1s
1.5×16h 2m 31s
1.75×13h 45m 1s
12h 1m 53s
Average video17m 11s
Longest57m
Shortest1m 48s
Compare Open on YouTube JSON

Plan to finish

About 25 days at an hour a day

Pick a daily pace and the days you'll watch. Ticked videos are skipped.

Days

At one hour a day, every day, this playlist takes about 25 days. Turn on JavaScript to plan around your week.

Videos (84)

1d 4m in total · tick what you've watched

Tick videos you've watched — progress is saved in this browser.

Videos to
Watched
1 1. Introduction to Algorithms 11:49 2018-01-18
2 1.1 Priori Analysis and Posteriori Testing 1:48 2018-03-04
3 1.2 Characteristics of Algorithm 5:37 2018-01-18
4 1.3 How Write and Analyze Algorithm 10:37 2018-01-18
5 1.4 Frequency Count Method 12:22 2018-01-18
6 1.5.1 Time Complexity #1 9:44 2018-01-18
7 1.5.2 Time Complexity Example #2 14:13 2018-01-18
8 1.5.3 Time Complexity of While and if #3 21:54 2018-02-01
9 1.6 Classes of functions 3:10 2018-01-18
10 1.7 Compare Class of Functions 5:11 2018-01-18
11 1.8.1 Asymptotic Notations Big Oh - Omega - Theta #1 15:46 2018-01-18
12 1.8.2 Asymptotic Notations - Big Oh - Omega - Theta #2 10:07 2018-01-18
13 1.9 Properties of Asymptotic Notations 11:58 2018-01-19
14 1.10.1 Comparison of Functions #1 9:28 2018-01-19
15 1.10.2 Comparison of Functions #2 10:26 2018-01-19
16 1.11 Best Worst and Average Case Analysis 18:56 2018-01-21
17 1.12 Disjoint Sets Data Structure - Weighted Union and Collapsing Find 26:04 2018-04-04
18 2 Divide And Conquer 7:04 2018-01-22
19 2.1.1 Recurrence Relation (T(n)= T(n-1) + 1) #1 13:43 2018-01-22
20 2.1.2 Recurrence Relation (T(n)= T(n-1) + n) #2 16:00 2018-01-23
21 2.1.3 Recurrence Relation (T(n)= T(n-1) + log n) #3 12:25 2018-01-23
22 2.1.4 Recurrence Relation T(n)=2 T(n-1)+1 #4 10:42 2018-01-24
23 2.2 Masters Theorem Decreasing Function 8:10 2018-01-24
24 2.3.1 Recurrence Relation Dividing Function T(n)=T(n/2)+1 #1 8:41 2018-01-24
25 2.3.2 Recurrence Relation Dividing [ T(n)=T(n/2)+ n]. #2 7:26 2018-01-26
26 2.3.3 Recurrence Relation [ T(n)= 2T(n/2) +n] #3 11:20 2018-01-26
27 2.4.1 Masters Theorem in Algorithms for Dividing Function #1 16:50 2018-01-26
28 2.4.2 Examples for Master Theorem #2 5:41 2018-01-26
29 2.5 Root function (Recurrence Relation) 5:37 2018-01-26
30 2.6.1 Binary Search Iterative Method 19:36 2018-01-29
31 2.6.2 Binary Search Recursive Method 7:11 2018-01-29
32 2.6.3 Heap - Heap Sort - Heapify - Priority Queues 51:08 2019-03-08
33 2.7.1 Two Way MergeSort - Iterative method 20:19 2018-01-31
34 2.7.2. Merge Sort Algorithm 20:23 2018-01-31
35 2.7.3 MergeSort in-depth Analysis 13:28 2018-02-01
36 2.8.1 QuickSort Algorithm 13:43 2018-02-02
37 2.8.2 QuickSort Analysis 11:37 2018-02-02
38 2.9 Strassens Matrix Multiplication 23:40 2018-02-06
39 3. Greedy Method - Introduction 12:02 2018-02-06
40 3.1 Knapsack Problem - Greedy Method 15:30 2018-02-06
41 3.2 Job Sequencing with Deadlines - Greedy Method 13:29 2018-02-07
42 3.3 Optimal Merge Pattern - Greedy Method 9:33 2018-02-07
43 3.4 Huffman Coding - Greedy Method 17:33 2018-02-08
44 3.5 Prims and Kruskals Algorithms - Greedy Method 20:12 2018-02-09
45 3.6 Dijkstra Algorithm - Single Source Shortest Path - Greedy Method 18:35 2018-02-09
46 4 Principle of Optimality - Dynamic Programming introduction 14:52 2018-02-16
47 4.1 MultiStage Graph - Dynamic Programming 21:07 2018-02-16
48 4.1.1 MultiStage Graph (Program) - Dynamic Programming 14:26 2018-03-04
49 4.2 All Pairs Shortest Path (Floyd-Warshall) - Dynamic Programming 14:13 2018-02-16
50 4.3 Matrix Chain Multiplication - Dynamic Programming 23:00 2018-02-16
51 [New] Matrix Chain Multiplication using Dynamic Programming Formula 52:02 2019-05-12
52 4.3.1 Matrix Chain Multiplication (Program) - Dynamic Programming 18:40 2018-03-05
53 4.4 Bellman Ford Algorithm - Single Source Shortest Path - Dynamic Programming 17:12 2018-02-16
54 4.5 0/1 Knapsack - Two Methods - Dynamic Programming 28:24 2018-02-20
55 4.5.1 0/1 Knapsack Problem (Program) - Dynamic Programming 17:00 2018-03-04
56 4.6 Optimal Binary Search Tree (Successful Search Only) - Dynamic Programming 30:19 2018-02-22
57 4.6.2 [New] Optimal Binary Search Tree Successful and Unsuccessful Probability - Dynamic Programming 57:00 2019-04-02
58 4.7 [New] Traveling Salesman Problem - Dynamic Programming using Formula 17:18 2018-04-02
59 4.8 Reliability Design - Dynamic Programming 26:32 2018-04-11
60 4.9 Longest Common Subsequence (LCS) - Recursion and Dynamic Programming 23:35 2018-04-19
61 5.1 Graph Traversals - BFS & DFS -Breadth First Search and Depth First Search 18:31 2018-02-24
62 5.2 Articulation Point and Biconnected Components 8:37 2018-02-24
63 6 Introduction to Backtracking - Brute Force Approach 8:15 2018-02-24
64 6.1 N Queens Problem using Backtracking 13:41 2018-02-24
65 6.2 Sum Of Subsets Problem - Backtracking 12:19 2018-02-24
66 6.3 Graph Coloring Problem - Backtracking 15:52 2018-02-26
67 6.4 Hamiltonian Cycle - Backtracking 18:35 2018-04-07
68 7 Branch and Bound Introduction 9:40 2018-02-26
69 7.1 Job Sequencing with Deadline - Branch and Bound 10:56 2018-02-26
70 7.2 0/1 Knapsack using Branch and Bound 10:48 2018-02-26
71 7.3 Traveling Salesman Problem - Branch and Bound 24:42 2018-04-13
72 8. NP-Hard and NP-Complete Problems 31:53 2018-02-28
73 8.1 NP-Hard Graph Problem - Clique Decision Problem 17:14 2018-04-09
74 9.1 Knuth-Morris-Pratt KMP String Matching Algorithm 18:56 2018-03-25
75 9.2 Rabin-Karp String Matching Algorithm 23:50 2018-03-30
76 10.1 AVL Tree - Insertion and Rotations 43:08 2018-03-16
77 10.2 B Trees and B+ Trees. How they are useful in Databases 39:41 2018-03-30
78 Asymptotic Notations - Simplified 22:44 2015-09-17
79 Hashing Technique - Simplified 17:04 2015-09-16
80 Shortest Path Algorithms (Dijkstra and Bellman-Ford) - Simplified 26:13 2016-12-22
81 BFS DFS - Simplified 19:13 2015-10-23
82 Tower of Hanoi Problem - Made Easy 9:32 2014-05-07
83 Row-Major and Column-Major Mapping 19:16 2015-09-16
84 Merge Sort Algorithm - Hindi 16:38 2015-09-10

Embed a badge

Show the watch time in a README or course description — it links back here and updates itself

Watch time: 1d 4m · 84 videos

Markdown
[![Watch time: 1d 4m · 84 videos](https://playlistduration.com/badge/playlist/PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O.svg)](https://playlistduration.com/playlist/PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O)
HTML
<a href="https://playlistduration.com/playlist/PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O"><img src="https://playlistduration.com/badge/playlist/PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O.svg" alt="Watch time: 1d 4m · 84 videos" width="196" height="20"></a>

Add ?speed=1.5 to the image URL for the time at that speed, ?label=Course to change the left text, or ?style=flat-square for square corners.

Want the numbers themselves? GET https://playlistduration.com/api/v1/playlist/PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O returns them as JSON — free, no key. API docs →

Data from the YouTube Data API as of 2026-09-22 (cached). Private or deleted videos are excluded from totals.