Category · Computer Science
Algorithms without fear: from Big O to graphs
A course of about 12 lessons with examples in JavaScript. Available now: Big O, arrays and hash tables, two pointers and sliding window, stack and queue, binary search, recursion, sorting, trees. Planned next: heaps, graphs (BFS and DFS), dynamic programming, greedy algorithms.
8 lessons120 min
To the first lessonCheatsheet nowTopics, each as its own lesson
01Big O: how to estimate the speed of codeDemoWe count not seconds, but how the work grows with the data.
14 min
02Arrays and hash tablesWhy index access is instant while search is not, and how a Map saves you from nested loops.
15 min
03Two pointers and sliding windowTwo techniques that turn checking every pair into a single pass.
15 min
04Stack and queueTwo simple structures behind undo, parsers and graph traversal.
14 min
05Binary searchHow to find an element among a million in twenty steps.
15 min
06Recursion: a function that calls itselfBase case, the call stack and a first look at memoization.
15 min
07Sorting: merge sort, quick sort and the built-in sortHow the two main algorithms work and what arr.sort() costs in JavaScript.
16 min
08Trees: binary tree, BST and traversalsNodes, height, four ways to walk a tree and search in O(log n).
16 min0/8 topics open. This is the course intro, not the whole course on one page.