Dynamic Programming Full Course | Visual Explanation | Leetcode

In this video, I have explained the concepts of Dynamic programming using Visualization, which makes it easy to grasp the underlying concepts.

First, the concept behind dynamic programming has been explained using the Fibonacci series as an example. Then, several famous Dynamic Programming problems have been explained and divided in the chapter that you can click and watch.

For most of the problems, there is an equivalent coding problem that is also available on Leetcode, whose links are also provided below that you can check out.

LeetCode Problem Links:-

Fibonacci Number:-https://leetcode.com/problems/fibonacci-number/

Longest Increasing Subsequence:- https://leetcode.com/problems/longest-increasing-subsequence/description/

Longest Common Subsequence:- https://leetcode.com/problems/longest-common-subsequence/description/

coin change (Minimum coins needed) :- https://leetcode.com/problems/coin-change/description/

Coin Change (Total Possible ways) :-https://leetcode.com/problems/coin-change-ii/description/

Climbing stairs:- https://leetcode.com/problems/climbing-stairs/description/

Implementation Link:-https://github.com/ByteQuest0/Implemention_codes/blob/main/Dynamic%20Programming/

Animation Code:- https://github.com/ByteQuest0/Animation_codes/blob/main/2025/

Tools used to make the video: Manim and Premiere Pro,.
manim link:- https://pypi.org/project/manimgl/
chapters:-
0:00 Dynamic Programming Introduction
7:37 0/1 Knapsack Problem
15:50 Coin Change (Minimum Coins Needed)
19:33 Coin Change Problem (Number of Ways)
23:16 Longest Increasing Subsequence
28:26 Longest Common Subsequence
34:07 Matrix Chain Multiplication

Видео Dynamic Programming Full Course | Visual Explanation | Leetcode канала ByteQuest