Sliding Window Median | Part 4 | Brute → Optimized Approach

Sliding Window Median | Part 4 | Brute → Optimized Approach Welcome to Part 3 of our Sliding Window series! In this video, we’ll solve the Sliding Window Median problem using 2 different approaches — starting with the Brute Force approach and then moving towards an Optimized solution. Approaches Covered: 🔹 Approach 1 – Brute Force Maintain the current window Sort the elements of each window Calculate the median Time Complexity: O(n × k log k) 🔹 Approach 2 – Optimized Efficiently maintain the elements of the sliding window Avoid sorting the complete window every time Use appropriate data structures to efficiently find the median Improved time complexity compared to the brute-force approach 💡 What You’ll Learn: How to calculate the median of a sliding window How to optimize repeated sorting operations How to think about maintaining dynamic window data Brute → Optimized problem-solving approach 📚 Sliding Window Playlist: Follow the complete playlist to learn Sliding Window problems step-by-step, from Brute Force to Optimized approaches. Channel: Raj Code's | CP | DSA Here, we cover Data Structures, Algorithms, Competitive Programming, LeetCode, CSES, and interview-oriented DSA problems with clear explanations and optimized solutions. If you find this video helpful, Like, Share & Subscribe to Raj Code's | CP | DSA for more DSA & Competitive Programming content! 🔔 Turn on notifications so you don’t miss the next part! #SlidingWindow #SlidingWindowMedian #DSA #Java #CompetitiveProgramming #LeetCode #DataStructures #Algorithms #Coding #DSAInJava #RajCodes #CP #DSA