Welcome to the next video of our DSA Course, where we dive into the concept of DYNAMIC PROGRAMMING.

In this video, We'll break down how DP stores solutions to subproblems to avoid redundant calculations.

We will solve classic DP problems like Fibonacci Sequence and Longest Common Subsequence, with clear
explanations. Learn how to recognize situations where DP can be applied to optimize your code.

Explore different DP approaches (top-down vs. bottom-up) and choose the best fit for your problem. And discover how DP is used in various coding scenarios, from bioinformatics to text editing.

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Dynamic Programming or DP
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Dynamic Programming (DP) Tutorial with Problems
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Greedy Approach vs Dynamic programming
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Chapters
00:00 - Introduction
00:10 - What is Dynamic Programming?
00:43 - Fibonacci Series in Dynamic Programming
07:25 - How to DP Solutions?
09:07 - Forming a recurrence relation
09:34 - Optimal Sub-problem
11:41 - Overlapping Subproblem
12:47 - Top Down DP (Recursion + Memorisation)
16:54 - Bottom up (tabulation)
20:45 - DP problem (Conclusion)

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🔴 Check out the video on RECURSION | What is RECURSION?
🔴 Check out the Full DSA Course Playlist: • DSA Course | Data Structures & Algori...

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