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📘 Welcome to Part 197 of Code & Debug’s DSA in Python Course! In this video, we tackle the classic Unique Paths II problem from LeetCode, where the robot must navigate from the top-left to the bottom-right of a grid, but with a twist, obstacles may block certain cells! We carefully walk through all 4 major dynamic programming solutions, moving from brute-force recursion to the most space-optimized DP, exactly as detailed in our in-depth article. This problem is an excellent way to learn how dynamic programming adapts to real-world constraints like obstacles and forbidden paths, making it a favorite in interviews. 🏫 What’s covered in this video: 1. Full problem statement and constraints 1. Approach 1: Brute Force Recursion 1. Approach 2: Memoization (Top-Down DP) 1. Approach 3: Tabulation (Bottom-Up DP) 1. Approach 4: Space-Optimized Tabulation 1. Step-by-step code walkthrough for each approach in Python 1. Visual dry run examples for path calculation with obstacles 1. Time and space complexity of each approach 1. Interview tips for handling variation in grid-based DP problems By the end, you'll confidently solve grid pathfinding problems with dynamic constraints, a must-have DP skill! 🔗 LeetCode Problem – Unique Paths II: https://leetcode.com/problems/unique-paths-ii/description/ 🔗 Blog Article with All 4 DP Solutions & Explanations: https://codeanddebug.in/blog/unique-paths-ii/ 📄 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 🔔 #UniquePathsII #DynamicProgramming #GridDP #LeetCode63 #ObstacleGrid #PythonDSA #Tabulation #Memoization #SpaceOptimization #CodeAndDebug #Part197 #DPPatterns #InterviewPrep
