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01. Algorithms Full Course || Design and Analysis of Algorithms | 11:59:23 | Tim Roughgarden | Stanford University | Computer Scientist | Geek's Lesson

In mathematics and computer science, an algorithm is a finite sequence of well-defined, computer-implementable instructions, typically to solve a class of problems or to perform a computation.

In this course you will learn about the design and analysis of #algorithms.

⭐️ Table of Contents ⭐️

0:00:03 Why study algorithms

0:04:18 Integer multiplication

0:12:56 Karatsuba multiplication

0:25:35 Merge sort

0:34:20 Merge sort pseudocode

0:47:11 Merge sort analysis

0:56:13 Principles for analysis of algorithms

1:11:29 Big oh notation

1:15:38 Basic examples

1:19:53 Big omega and theta

1:27:24 Additional examples

1:35:15 Log n algorithm

1:40:41 Subcubic matrix multiplication algorithm

3:35:52 Quicksort overview

4:04:44 Partitioning around a pivot

4:23:29 Choosing a good pivot

4:33:29 A decomposition principle

4:55:17 Algorithm analysis: key insights

5:16:01 Randomized selection

5:50:18 Deterministic selection

6:29:16 Omega log n lower bound for comparison

6:42:46 Graphs and minimum cuts

6:58:37 Graphs representation

7:12:59 Random contraction algorithm

7:21:44 Analysis of contraction algorithm

7:51:48 Counting minimum cuts

7:59:06 Graph search overview

8:22:26 Breadth first search

8:57:41 Depth first search

9:05:05 Topological sort

9:45:48 Dijkstra's algorithm

10:22:39 Data Structures

10:27:15 Heaps operations

10:45:27 Balanced search tree

10:56:22 Binary search tree

⭐️ Credit ⭐️

Course Provided by: Stanford Algorithms

Course Author: Professor Tim Roughgarden

This course is provided here only for educational purpose.

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Tuesday, March 31, 2020

MIT OpenCourseWare, Algorithm, MIT, OCW, 1 of 47

1. Algorithmic Thinking, Peak Finding

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