Master datastructures.Watch them move. Then build them.
Every concept has an interactive animated visualizer — watch algorithms run step by step, not just read about them. Free, beginner-to-advanced, no fluff.
Stop reading about algorithms.
Press play and watch a sort actually run — compares, swaps, and all. Every page on this course has a widget like this.
The crash course
Never studied DSA before? Start here. Twelve focused lessons that take you from “what is an array?” to confidently reading Big-O notation and writing your first recursive function. Each one is short, punchy, and has a built-in visualizer.
What Is a Data Structure?
A data structure is a deal you strike — you give up something to make one operation fast. Here is the big picture before you dive into any of them.
Big-O Notation, Demystified
Big-O notation is the one tool every engineer needs to reason about performance. Learn to read it, use it, and stop fearing it — with concrete op-counts that make the curves click.
Arrays and How Memory Really Works
Go under the hood of the most fundamental data structure — contiguous bytes, O(1) index addressing, cache lines, and why a sequential scan beats a random walk every time.
Recursion: Thinking in Smaller Selves
Recursion from first principles — base case, recursive case, and the call stack — the mental model you need before trees, graphs, and DP.
Data structures
One article per structure, each with an interactive visualizer you can actually play with. Insert nodes, delete edges, watch the rebalancing happen live. Then read the explanation that makes sense of what you just saw.
Skip Lists: The Structure Redis Chose Over Balanced Trees
Skip lists replace tree rotations with coin flips: expected O(log n) search, insert, and delete in ~40 lines. Why Redis, LevelDB, and Java picked them.
Union-Find (Disjoint Set Union)
Union-Find (disjoint set union) answers 'are these two nodes connected?' in near-constant time. Master path compression, union by rank, and Kruskal's MST.
Tries (Prefix Trees)
How tries (prefix trees) power autocomplete and spell-check — insert, search, and prefix queries all run in O(L) on word length, not dictionary size.
Strings
Strings are immutable arrays hiding an O(n²) concatenation trap. Learn the sliding window, two-pointer, and hashing patterns that crack string interviews.
Segment Trees
Segment trees answer range queries AND handle point or range updates in O(log n) — the structure to reach for when prefix sums aren't enough and you need both reads and writes at scale.
LRU Cache
Implement an LRU cache with O(1) get and put: hash map plus doubly linked list, full Python code, eviction mechanics, and the interview traps.
Techniques & patterns
Sliding window, two pointers, binary search on the answer, backtracking, dynamic programming — the fifteen patterns that show up in 80% of coding interviews. Each guide walks through the template, then applies it to real problems.
String Matching: KMP and Rabin-Karp Without the Mysticism
String matching without mysticism: derive KMP's failure function, Rabin-Karp's rolling hash with honest collision math, and the four LeetCode classics.
Monotonic Queue: Sliding Window Maximum in O(n)
Learn the monotonic queue: the deque discipline that solves Sliding Window Maximum in O(n) and collapses windowed DP like Jump Game VI from O(nk) to O(n).
Topological Sort
Order the nodes of a DAG so every edge points forward — the algorithm that drives build systems, package managers, course schedulers, and anything else that lives and dies by dependency ordering.
The Top-K Elements Pattern
How a heap of size k gives you the k largest (or smallest, or most frequent) items in O(n log k) — and why a min-heap is the counterintuitive tool for finding the biggest things.
Subsets, Permutations & Combinations
Generate subsets, permutations, and combinations with one choose/explore/un-choose backtracking template — and know exactly where 2^n and n! hit the wall.
Shortest Paths (Dijkstra, Bellman-Ford, BFS)
Pick the right shortest-path algorithm: BFS for unweighted graphs, Dijkstra for non-negative weights, Bellman-Ford for negative edges — with every gotcha.
Find what you need, fast
Every article is tagged. Jump straight to the topic you want to study or review.
See it. Understand it.
Keep it.
The fastest way to learn a data structure is to watch it work. Ironclad Academy gives you interactive visualizers for everything, paired with explanations written by people who actually care about teaching well. It's free. Always will be.