Hustle & Code – Day 18/25 🔥 Heaps in Java (Min & Max Heap) + LeetCode Heap Problems.

🚀 Day 18 of my 25-Day Coding Challenge is complete!
Today I dived into the world of Heaps in Java — one of the most powerful and commonly used data structures in problem-solving and coding interviews.

Here’s what I covered today:
✅ Understanding the Heap Data Structure (Complete Binary Tree + Heap Property)
✅ Difference between Min Heap and Max Heap
✅ Implementation of Heap operations:

Insertion into a Heap

Deletion from a Heap

Heapify function
✅ Learning and applying Heap Sort using Max Heap

To strengthen the concepts, I solved two popular LeetCode Heap problems:
1️⃣ Kth Largest Element in an Array
2️⃣ Top K Frequent Elements

Both are classic problems that showcase the real power of priority queues and heaps in solving complex tasks efficiently.

This challenge is all about building:
💻 Strong DSA foundations in Java
📈 Consistency in solving LeetCode problems
🔥 Confidence for placement and coding interviews

👉 Next up: I’ll be learning Graph Basics and solving Graph-related LeetCode problems. Stay tuned!

Видео Hustle & Code – Day 18/25 🔥 Heaps in Java (Min & Max Heap) + LeetCode Heap Problems. канала Hustle and Code