2016
Pluralsight
Rasmus Amossen
4h 09m
English
An introductory guided tour to the field of data structures, algorithms, and complexity analysis. This course is loaded with a ton of practical examples, and focuses on intuition, rather than formulas and mathematical proofs.
The phrase "Get Great Performance for Free!" sounds like a quote from bad commercial, but when it comes to algorithms and data structures, that may actually be the case. This introductory course shows how the use of common data structures may simplify and even significantly impact performance of solutions to typical real-life everyday programming problems. The course gently introduces the viewer for "complexity analysis" which makes it possible to spot a poorly (and a great) performing program, even without the need for executing it. Complexity analysis is an invaluable tool or "language" for discussing performance with colleagues - and it's not even difficult. After having covered the most common data structures, the course continues to describe some general strategies (algorithms) to efficiently solve more high-level problems. Like with data structures, it is shown how a careful choice of problem solving strategy can dramatically reduce computation time. The last part of the course shifts the focus a bit and shortly teases a few popular theoretical subjects and explains, at a purely intuitive level, what the complexity classes P, NP, and the famous problem, P = NP, is all about.
FileName Size Length Bit rate Data rate Resolution Frame Rate Parent Folder
01.Strategies Matter 21.3 MB 0:07:27 76kbps 320.00 1280x720 15 frames/second 01 Introduction to Algorithms
01.Introduction 16.6 MB 0:08:18 75kbps 201.00 1280x720 15 frames/second 02 Measuring Performance
02.Asymptotic Performance 10.7 MB 0:05:08 75kbps 215.00 1280x720 15 frames/second 02 Measuring Performance
03.Big Theta 18.2 MB 0:09:36 75kbps 187.00 1280x720 15 frames/second 02 Measuring Performance
04.Big O 18.6 MB 0:11:46 72kbps 145.00 1280x720 15 frames/second 02 Measuring Performance
05.Big Omega 5.74 MB 0:02:40 71kbps 226.00 1280x720 15 frames/second 02 Measuring Performance
06.Recursive Methods 30.6 MB 0:13:57 75kbps 228.00 1280x720 15 frames/second 02 Measuring Performance
07.Amortized Complexity 4.46 MB 0:02:27 73kbps 178.00 1280x720 15 frames/second 02 Measuring Performance
08.Lessons Learned 4.94 MB 0:03:44 75kbps 106.00 1280x720 15 frames/second 02 Measuring Performance
01.Introduction 28.0 MB 0:09:39 77kbps 326.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
02.Dynamic Arrays 16.8 MB 0:10:25 77kbps 145.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
03.Linked Lists 22.1 MB 0:08:28 77kbps 286.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
04.Priority Queues 20.8 MB 0:10:21 76kbps 202.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
05.Hash Tables 35.3 MB 0:15:43 76kbps 234.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
06.Lessons Learned 10.0 MB 0:04:15 77kbps 251.00 1280x720 15 frames/second 03 Organizing Data Efficiently with Common Data Structures
01.Introduction 4.55 MB 0:02:34 74kbps 170.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
02.Graph Traaversal 31.9 MB 0:14:47 75kbps 224.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
03.Brute Force and Greedy Algorithms 14.6 MB 0:08:36 74kbps 160.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
04.Divide and Conquer 26.4 MB 0:12:21 70kbps 225.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
05.Dynamic Programming One 16.3 MB 0:05:22 73kbps 349.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
06.Dynamic Programming Two 58.2 MB 0:24:23 73kbps 257.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
07.Branch and Bound 40.4 MB 0:18:32 71kbps 230.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
08.Lessons Learned 12.8 MB 0:04:46 73kbps 300.00 1280x720 15 frames/second 04 Operating on Data Efficiently with Common Algorithms
01.Introduction 2.32 MB 0:01:37 77kbps 121.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
02.Input Size in Bits 11.7 MB 0:05:46 75kbps 207.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
03.P vs. NP One 18.8 MB 0:10:48 73kbps 168.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
04.P vs. NP Two 13.6 MB 0:04:54 72kbps 313.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
05.Heuristics and Approximation Algorithms 14.9 MB 0:07:21 73kbps 206.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
06.Lessons Learned 7.91 MB 0:04:07 74kbps 191.00 1280x720 15 frames/second 05 Looking Ahead to Some Very Hard Problems
Download File Size:575.99 MB
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