Coursera course offered by Standford University

Course Topics Part I

Vocabulary for design and analysis of algorithms E.g., "Big-Oh" notation; "sweet spot" for high-level reasoning about algorithms

Divide and conquer algorithm design paradigm Apply to: Integer multiplication, sorting, matrix multiplication, closet pair General analysis methods("Master method/Theorem")

Randomization in algorithm design Apply to: QuickSort, primality testing, graph partitioning, hashing

Primitives for reasoning about graphs Connectivity information, shortest paths, structure of information and social networks

Use and implementation of data structures Heaps, Balanced binary search trees, hashing and some variants(e.g., bloom filters)

Course Topics Part II

Greedy algorithm design paradigm

Dynamic programming algorithm design paradigm

NP-complete problems and what to do about them

Fast heuristics with provable guarantees

Fast exact algorithms for special cases

Exact algorithms that beat brute-force search