◇DSA Prep
Patterns, data structures, algorithms — the canonical interview-prep notes.
foundations.md~7m00 — Foundations: Big O, Complexity, Python & C++ Idioms
1. Big O — what it really measures
arrays-hashing.md~7m01 — Arrays & Hashing
1. Arrays — the underlying memory
two-pointers.md~6m02 — Two Pointers
1. The core idea
sliding-window.md~5m03 — Sliding Window
1. The intuition
stack.md~6m04 — Stack
1. Stack basics
binary-search.md~7m05 — Binary Search
1. The core idea
linked-list.md~7m06 — Linked List
1. What a linked list is
trees.md~8m07 — Trees
1. Tree terminology
tries.md~5m08 — Tries (Prefix Trees)
1. What a trie is
heaps.md~7m09 — Heaps & Priority Queues
1. Heap conceptually
backtracking.md~5m10 — Backtracking
1. What backtracking is
graphs.md~7m11 — Graphs
1. Graph terminology
advanced-graphs.md~7m12 — Advanced Graphs
1. When to use what (decision tree)
dp-1d.md~8m13 — Dynamic Programming (1D)
1. What DP really is
dp-2d.md~6m14 — Dynamic Programming (2D)
1. When you need 2D DP
greedy-intervals.md~7m15 — Greedy & Intervals
1. What greedy is
bit-manipulation.md~6m16 — Bit Manipulation
1. Binary basics
patterns-cheatsheet.md~5m17 — Patterns Cheatsheet
1. The Trigger Lookup Table
interview-strategy.md~10m18 — Interview Strategy (How to Actually Pass)
1. The UMPIRE method
readme.md~4mDSA Prep — Comprehensive Reference
Complete reference for Data Structures and Algorithms aligned with the Neetcode 150 weekly schedule. Each file is a deep dive with intuition, ASCII diagrams, Python (and C++ where useful) implementations, complexity a…