Introduction to Algorithms (CLRS) | Computer Science Fundamentals | Oh My Learning

01 Asymptotic growth and Big-O/Theta/Omega 8 min read junior drafted 02 Recurrences and the Master method 9 min read mid drafted 03 Divide and conquer as a design paradigm 7 min read mid drafted 04 Probabilistic analysis and randomized algorithms 8 min read senior drafted 05 Elementary data structures (stacks, queues, linked lists) 8 min read junior drafted 06 Hash tables and expected-time lookup 8 min read junior drafted 07 Heaps and priority queues 8 min read mid drafted 08 Quicksort and randomized partitioning 7 min read mid drafted 09 Balanced search trees (red-black trees) 8 min read mid drafted 10 Order statistics and selection in linear time 8 min read senior drafted 11 Dynamic programming fundamentals 9 min read mid drafted 12 Greedy algorithms and exchange arguments 9 min read mid drafted 13 Graph representations, BFS, and DFS 9 min read mid drafted 14 Shortest-path algorithms 9 min read mid drafted 15 Minimum spanning trees 8 min read mid drafted 16 Maximum flow and the max-flow min-cut theorem 9 min read senior drafted 17 Amortized analysis techniques 9 min read senior drafted 18 Disjoint sets and union-find analysis 8 min read mid drafted 19 NP-completeness and polynomial-time reductions 9 min read senior drafted 20 Approximation algorithms for NP-hard problems 8 min read senior drafted