data structures & algorithms (patterns)
the structures that run production and the patterns that close interviews. balanced trees, b-trees, graphs, and dynamic programming. part 2 of 3.
19 lessons|5 modules|~4 hours
what you’ll learn
- understand the balanced trees, b-trees, and skip lists behind databases and redis
- compose structures into the lru and lfu caches real systems run on
- solve graph problems with topological sort, dijkstra, and minimum spanning trees
- recognise and apply backtracking and dynamic programming patterns on sight
- close the gap with intervals, bit tricks, and a repeatable way to attack any problem
curriculum
planning sketchthis is a rough curriculum we’re still planning. modules and lessons are likely to shift before any lesson is recorded. want to shape it? mail@karnstack.com.
01
module one
balanced and specialized trees
48 min4 lessons01balanced trees: avl, red-black, and why your map uses onecoming soon14m
02tries: prefix trees and where autocomplete comes fromcoming soon9m
03b-trees and b+ trees: how every database index workscoming soon14m
04skip lists: how redis sorted sets workcoming soon11m
checkpoint
module quiz · balanced and specialized trees
5 questions · ~5m · test your recall before moving on
02
module two
structures that run production
31 min3 lessons05union-find: disjoint sets and path compressioncoming soon10m
06lru and lfu caches: composing structurescoming soon11m
07bloom filters and probabilistic structurescoming soon10m
checkpoint
module quiz · structures that run production
5 questions · ~5m · test your recall before moving on
03
module three
graph algorithms
33 min3 lessons08topological sort: ordering under dependenciescoming soon9m
09shortest paths: dijkstra and bellman-fordcoming soon14m
10minimum spanning trees: kruskal and primcoming soon10m
checkpoint
module quiz · graph algorithms
5 questions · ~5m · test your recall before moving on
04
module four
backtracking and dynamic programming
74 min6 lessons11backtracking: subsets, permutations, combinations, one templatecoming soon13m
12what dp actually is: memoization becomes tabulationcoming soon14m
131d dp patterns: kadane, house robber, climbing stairscoming soon11m
142d dp patterns: grids, knapsack, edit distancecoming soon14m
15sequence dp: lcs and liscoming soon10m
16greedy vs dp: when greedy is provably correctcoming soon12m
checkpoint
module quiz · backtracking and dynamic programming
5 questions · ~5m · test your recall before moving on
05
module five
the patterns that close the gap
37 min4 lessons17intervals: merge, insert, and the sweep linecoming soon10m
18bit manipulation and the math you actually needcoming soon11m
19non-comparison sorts: counting, radix, bucketcoming soon9m
--how to approach any problem + what to learn nextcoming soon7m
checkpoint
module quiz · the patterns that close the gap
5 questions · ~5m · test your recall before moving on
frequently asked
- when does this launch?
- in planning, sequenced after foundations. the curriculum on this page is a sketch. modules and lessons are likely to shift before any lesson is recorded.
- do i need part 1 first?
- ideally yes. this part assumes you're fluent with arrays, hashing, trees, heaps, and basic graph traversal. equivalent experience works just as well.
how this course is made
the curriculum is curated by karnstack and reviewed by senior engineers in the industry before it ships. narration is an ai voice (elevenlabs) reading human-written, human-reviewed scripts. read how courses are made.