DSA & Algorithms

Space Complexity & Trade-offs

Every algorithm trades time for space, learn to navigate that trade-off

Two Pointers Technique

Turn O(n²) brute force into elegant O(n) solutions

Linked Lists

A chain of boxes, each one knows only where to find the next

Stacks

Last-in, first-out, the structure behind function calls, undo buttons, and expression parsing

Queues & Deques

First-in, first-out, the fairness principle behind BFS and task scheduling

Sorting Algorithms

From bubble sort to Tim sort, why algorithm choice matters

Merge Sort & Quick Sort

Divide and conquer, the strategy behind the fastest general-purpose sorts

Backtracking

Explore every possibility, but smartly prune dead ends

Hash Sets & Their Patterns

Membership testing in O(1), eliminating duplicates and tracking visited nodes

Binary Search Trees

Ordered trees that combine the speed of binary search with the flexibility of trees

Tree Traversals

DFS vs BFS, the two ways to visit every node in a tree

BFS & DFS on Graphs

Two essential traversal strategies, and when to use each

Core DP Patterns

Knapsack, longest subsequence, and matrix paths, the templates behind 80% of DP problems

Heaps & Priority Queues

Always-sorted access to the minimum or maximum, O(log n) insert, O(1) peek

Top Interview Patterns

The 5 pattern recognition skills that unlock 80% of coding interview problems