DSA in Python – Minimum Path Sum in Triangular Grid | 4 DP Approaches | LeetCode 120 | Part 199

📘 Welcome to Part 199 of Code & Debug’s DSA in Python Course!

In this lesson, we dive into Minimum Path Sum in Triangular Grid, LeetCode 120, a must-know for dynamic programming enthusiasts! The challenge: Given a triangle array, find the minimum path sum from top to bottom, stepping only to adjacent numbers on the row below. We’ll guide you through all 4 major DP paradigms – brute force recursion, memoization, tabulation, and space optimization, mirroring our detailed explanations from the blog.

Mastering this problem will help you ace a wide class of bottom-up and space-optimized DP interview questions, especially those involving non-standard grids and triangle-shaped structures.

👨🏫 What’s covered in this video:
1. Problem statement breakdown and sample walkthroughs
2. Approach 1: Brute Force Recursion
3. Approach 2: Memoization (Top-Down DP)
4. Approach 3: Tabulation (Bottom-Up DP)
5. Approach 4: Space-Optimized Tabulation (O(n) space)
6. Stepwise Python implementations for each method
7. Dry runs for intuition-building and state transitions
8. Comprehensive time & space complexity analysis

🔗 LeetCode Problem – Triangle:
https://leetcode.com/problems/triangle/description/

🔗 Detailed Article with Codes & Explanations:

Triangle | Leetcode 120 | All 4 DP Solutions

📄 FULL Playlist Sheet (Every Video Listed):
https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing

🎓 Enroll Free: Master Python DSA Course
https://codeanddebug.in/course/master-dsa-with-leetcode

🚀 Advance Python DSA for FAANG (Zero to Hero Course):
https://codeanddebug.in/course/zero-to-hero-python-dsa

Stay focused and keep coding with Code & Debug.
Like | Share | Subscribe | Hit the 🔔

#Triangle #MinimumPathSum #LeetCode120 #DynamicProgramming #BottomUpDP #Memoization #Tabulation #SpaceOptimization #PythonDSA #CodeAndDebug #Part199 #TriangleDP #DPPatterns #InterviewPrep