Algorithms design and analysis part 1(1/2)

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Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.

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TIME STAMP
0:00 Introduction Why Study Algorithms

18:34 About the course

35:53 merge sort Motivation and example

44:38 merge sort Pseudocode

57:29 merge sort Analysis

1:06:31 Guiding Principles for Analysis of Algorithms

1:21:48 Big-oh Notation

1:25:57 Basic Examples

1:33:24 Big Omega and Theta

1:40:55 Additional Examples [Review - Optional]

1:48:46 O(n log n) Algorithm for Counting Inversions 1

2:01:22 O(n log n) Algorithm for Counting Inversions 2

2:17:55 Strassens Subcubic Matrix Multiplication Algorithm

2:40:27 O(n log n) Algorithm for closest pair 1

3:12:14 O(n log n) Algorithm for closest pair 2

3:31:13 Motivation

3:39:00 Formal Statement

3:48:58 Examples

4:02:04 Proof 1

4:12:01 Interpretation of the 3 cases

4:22:47 Proof 2

4:39:03 Quicksort Overview

4:51:12 Partitioning Around a Pivot

5:16:08 Correctness of Quicksort [Review - optional ]

5:26:47 Choosing a Good Pivot

5:49:12 Analysis 1 A Decomposition Principle [Advance - Optional]

6:11:00 Analysis 2 the key Insight [Advance - Optional ]

6:22:47 Analysis 3 Final Calculations [Advance-Optional]

6:31:44 Part 1 [Review-Optional]

6:57:41 Part 2 [Review-Optional]

7:15:02 Randomized Selection - Algorithm

7:36:42 Randomized Selection - Analysis

7:57:17 Deterministic Selection -Algorithm [Advance-optional]

8:14:13 Deterministic Selection - Analysis 1 [Advance-optional]

8:36:15 Deterministic Selection - Analysis 2 [Advance-optional]

8:48:57 Omega (n log n) Lower Bound for comparison-Based Sorting [Advance-optional]

9:02:26 Graph and Minimum Cuts

9:18:17 Graph Representations

9:32:40 Random Contraction Algorithm


Algorithms design and analysis part 1(2/2)

Algorithms design and analysis part 2(1/2)

Algorithms design and analysis part 2(2/2)

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