A
IntermediateFull track availableFoundations
Algorithms & Data Structures
Big-O, arrays, hash maps, sorting, searching, and recursion — required for Mid-level
13 atomsSpaced repetitionLearn at your own pace
What you'll learn
Big-O notation — time and space complexity
Arrays & Hash Maps — tradeoffs, two-pointer, sliding window
Sorting — Timsort, merge sort, quicksort, bisect
Recursion — base cases, memoization, backtracking
Binary Search — iterative, bisect module, search-on-answer pattern
Stack — LIFO, push/pop, DFS, bracket matching, monotonic stack
Queue — FIFO, enqueue/dequeue, BFS, deque
Linked List — traversal, reversal, fast/slow pointers, dummy node
Two Pointers — converging, sliding window, fast/slow
Depth-First Search — trees, graphs, backtracking
Breadth-First Search — shortest path, level order, grid traversal
Heaps & Priority Queues — top-K, merging, scheduling
Dynamic Programming — memoization, tabulation, state & recurrence
What you can skip
Academic algorithms that almost never appear in interviews and are safe to skip: Kruskal's, Prim's, Ford-Fulkerson, Bellman-Ford, Boyer-Moore, KMP. If an algorithm is named after a person, it's almost certainly in this category. Source: AlgoMonster data-driven analysis.