Section	Name	Description
Topics and Lectures	Lecture #0: Intro
	Lecture #0: Intro (long)
	Lecture video #0: Intro
	Lecture #1: Approximation algorithms
	Lecture #1: Approximation algorithms (long)
	Lecture #2a: Exact algorithms
	Lecture #2a: Exact algorithms (long)
	Lecture #2b: Computational geometry
	Lecture #2b: Computational geometry (long)
	Lecture #3: Parameterized algorithms
	Lecture #3: Parameterized algorithms (long)
	Lecture #4: The push-relabel algorithm for the maximum flow problem
	Lecture #4: The push-relabel algorithm for the maximum flow problem (long)
	Lecture #5: Quadratic Program for MaxCut
	Lecture #5: Quadratic Program for MaxCut (long)
	Lecture #X: Rearrangemnet distance of phylogenetic trees
	Lecture #X: Rearrangemnet distance of phylogenetic trees (long)
	Lecture #6: Randomized algorithms (long)
	Lecture #6: Randomized algorithms
	Lecture #7: Online Algorithms
	Lecture #7: Online Algorithms (long)
	Lecture #8: Succinct data structures
	Lecture #8: Succinct data structures (long)
	Lecture #9: Optimal Binary Search Trees and Splay Trees
	Lecture #9: Optimal Binary Search Trees and Splay Trees (long)
	Lecture #10: string matching (long)
	Lecture #10: string matching
	Lecture #11: probabilistic data structures
	Lecture #11: probabilistic data structures (long)
	Lecture #12: Algorithms in Practice
	Lecture #12: Algorithms in Practice (long)
Exercises	LaTeX template for exercise submissions
Literature and Additional Materials	[Mann '17] The Top Eight Misconceptions about NP-Hardness
	[Goldberg, Tarjan '88] A new approach to the maximum-flow problem
	[GW '95] Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
	[Jacobson '89] Space-efficient static trees and graphs