Introduction to Algorithms (MIT)

Slides of introduction to algorithms                                                                                   

0:00	Introduction to Algorithms - Lecture 1
1:22	Course information
17:18	Analysis of algorithms
21:59	Why study algorithms and performance?
27:39	The problem of sorting
29:20	Insertion sort (1)
32:24	Insertion sort (2)
34:27	Example of insertion sort (1)
34:39	Example of insertion sort (2)
34:48	Example of insertion sort (3)
34:53	Example of insertion sort (4)
34:57	Example of insertion sort (5)
35:06	Example of insertion sort (6)
35:11	Example of insertion sort (7)
35:20	Example of insertion sort (8)
35:23	Example of insertion sort (9)
35:28	Example of insertion sort (10)
35:32	Example of insertion sort (11)
36:17	Running time
39:28	Kinds of analyses
46:49	Machine-independent time
50:32	Θ-notation
54:45	Asymptotic performance
57:00	Insertion sort analysis
63:35	Merge sort
65:24	Merging two sorted arrays (1)
66:18	Merging two sorted arrays (2)
66:31	Merging two sorted arrays (3)
66:39	Merging two sorted arrays (4)
66:42	Merging two sorted arrays (5)
66:46	Merging two sorted arrays (6)
66:49	Merging two sorted arrays (7)
66:51	Merging two sorted arrays (8)
67:13	Merging two sorted arrays (9)
67:16	Merging two sorted arrays (10)
68:20	Analyzing merge sort
70:48	Recurrence for merge sort
72:54	Recursion tree (1)
73:39	Recursion tree (2)
73:49	Recursion tree (3)
74:18	Recursion tree (4)
74:50	Recursion tree (5)
75:02	Recursion tree (6)
76:16	Recursion tree (7)
76:33	Recursion tree (8)
76:41	Recursion tree (9)
76:49	Recursion tree (10)
78:12	Recursion tree (11)
79:19	Conclusions

Video lectures: 6.064J/18.410J (MIT)

Course homepage
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.