REFERENCE
Data structures and algorithms roadmap
The AlgoPath roadmap lays out data structures and algorithms in the order they build on each other: 150 steps in 19 groups. Each row of groups needs only the rows above it, so groups that share a row can be taken in any order.
Topics in the order they build on each other
Tier 3
Tier 4
Tier 5
Tier 7
The first 33 lessons are free
Open any of them now. Each one reads and runs in the browser, no account needed.
- 0What is an algorithm?
- 1Instructions a computer follows exactly
- 2Data and variables: a labeled box
- 3A list: a row of numbered boxes
- 4Doing it for everyone: loops
- 5Making choices: if / else
- 6Your first program: add two numbers
- 7Find the biggest number
- 8Why some ways are faster
- 9Big-O: a name for how fast the work grows
- 10Rearranging an array without a second one
- 11Sets: a bag that refuses duplicates
- 12Map: a labeled store of key → value
- 13WeakMap and WeakSet: attach data to objects
- 14How a hash table finds a slot
- 15Collisions, handled by chaining
- 16Collisions, handled by probing (open addressing)
- 17Load factor and resizing
- 18"Have I seen this?" in one step
- 19Closing in from both ends
- 20Squeezing out duplicates in place
- 21Reusing the last window's work
- 22A window that changes size to fit a rule
- 23A window that remembers what's inside it
- 24Adding up any stretch of a list in one step
- 25Counting the stretches that add up to k
- 26Summing any rectangle in one step
- 27Bumping a whole range without touching every slot
- 28Finding an item by scanning a list
- 29Finding one item in a sorted list by halving
- 30Finding the exact spot where "no" turns into "yes"
- 31Binary search in a rotated sorted array
- 32Guessing the answer, then binary-searching the guess