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📘 Welcome to Part 195 of Code & Debug’s DSA in Python Course! In this video, we tackle the classic 2D dynamic programming problem: Geek's Training from GeeksforGeeks. Each day, Geek must choose between Running, Fighting, and Learning, but cannot perform the same activity on consecutive days. We'll implement all 4 approaches, evolving from pure recursion to the optimal space-optimized DP solution, just as explained in our companion article. This is a perfect exercise to master DP state management by introducing an extra dimension (task/day), frequently seen in advanced DP interview questions. 👨🏫 What's covered in this video: 1. Problem statement and key constraints 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 6. Full Python code walkthrough for each approach 7. Dry run examples & transition explanations 8. State definition: f(day, last_task) 9. Complexity analysis and summary 10. Interview tips on how “activity restriction” drives DP state By the end of this session, you’ll confidently model and solve complex 2D DP problems! 🔗 GFG Problem – Geek’s Training: https://www.geeksforgeeks.org/problems/geeks-training/1 🔗 In-depth Article with Code and Explanations: https://codeanddebug.in/blog/geeks-training/ 📄 Full Playlist Sheet (All Questions in Order): https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 🎓 Enroll in the FREE 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 🔔 #GeeksTraining #DynamicProgramming #2DDP #Memoization #Tabulation #SpaceOptimization #PythonDSA #GFGPractice #CodeAndDebug #Part195 #ActivitySelection #DSAPatterns #InterviewPrep
