Course Schedule

The schedule shows all course meetings (lectures and recitations) and important dates (release/due dates and exams). See the Lecture Schedule and Recitation Schedule for focused schedules.

Week	Short Name	Date	Topic	References	Released	Due
1	L01	Th 1/8	Algorithms, asymptotic analysis	[Er0]
1	R01	F 1/9	Introduction
2	L02	Tu 1/13	Divide & Conquer I: Merge Sort and Recurrences	[DPV2,Er1]	HW1 out
2	L03	Th 1/15	Divide & Conquer II: Quicksort and Randomization	[Er1,Ed2]
2	R02	F 1/16	Divide & Conquer, Sorting
3	L04	Tu 1/20	Parallel Algorithms I: Concepts and Analysis	[CLRS27]	HW2 out	HW1 due
3	L05	Th 1/22	Parallel Algorithms II: Algorithm Design	[CLRS27]
3	R03	F 1/23	Parallel Algorithms
4	L06	Tu 1/27	Dynamic Programming I: Introduction, memoization	[DPV6,Er3]	HW3 out	HW2 due
4	L07	Th 1/29	Dynamic Programming II: Sequence Alignment, Dependency Graph	[DPV6,Er3]
4	R04	F 1/30	Dynamic Programming
5	L08	Tu 2/3	Dynamic Programming III: Matrix Multiplication, Trees	[DPV6,Er3]	HW4 out	HW3 due
5	L09	Th 2/5	Graph Traversal I: Depth-First Search, Connected Components	[DPV3,Er6]
5	R05	F 2/6	More DP and Graphs
6	L10	Tu 2/10	Graph Traversal II: Topological Sort, Strongly Connectivity	[DPV3,Er6]	HW5 out	HW4 due
6	L11	Th 2/12	Graph Traversal III: Breadth First Search	[DPV4,Er5]
6	R06	F 2/13	Graph Search
7	L12	Tu 2/17	Shortest Paths I: Dijkstra's Algorithm, A*	[DPV,Er8]	HW6 out	HW5 due
7	L13	Th 2/19	Shortest Paths II: Dynamic Programming	[DPV4,Er9]
7	R07	F 2/6	Exam I Review
8	E01	Tu 2/24	EXAM I (L01-L12)		HW7 out	HW6 due
8	L14	Th 2/26	Greedy I: Minimum Spanning Tree	[DPV4,Er7]
8	R08	F 2/27	Greedy Algorithms
9	L15	Tu 3/3	Greedy II: Compression, scheduling	[DPV5,Er4]		HW7 due
9	L16	Th 3/5	Cuts and Flows I: Max-flow and Min-cut	[Er10]
9	R08	F 3/6	More Greedy and Intro to Max-flows
		Tu 3/10	NO LECTURE (spring recess)
		Th 3/12	NO LECTURE (spring recess)
		F 3/13	NO RECITATION (spring recess)
10	L17	Tu 3/17	Cuts and Flows II: Algorithm, applications	[Er10,11]	HW8 out
10	L18	Th 3/19	Hardness I: Complexity Classes and NP-Completeness	[Er12]
10	R10	F 3/20	Max Flow Applications and Intractability
11	L19	Tu 3/24	Hardness II: NP-Complete Problems and Reductions	[DPV8,Er12]	HW9	HW8 due
11	L20	Th 3/26	Hardness III: Approximation algorithms	[DPV8,Er12]
11	R11	F 3/27	More Intractability
12	L21	Tu 3/31	Big Data 1: Clustering-Greedy	[Ph]	HW9 due	HW0 out
12	L22	Th 4/2	Big Data 2: Clustering-kmeans and randomized	[CLRS33,Ph8]
12	R12	F 4/3	Clustering
13	L23	Tu 4/7	Big Data 3: Hashing	[CLRS33,Ph8]		HW10 due
13	L24	Th 4/9	Big Data 4: Sketching	[Ph??]
13	R13	F 4/10	Exam II Review
14	E02	Tu 4/14	EXAM II (L13-L24)
		Wed 4/29	FINAL EXAM (2:00pm-5:0pm, cumulative)