Video Description
"Good and simple to understand introduction to algorithms."Boris Vasile, Team Lead, Garmin Cluj
Algorithms - established processes for solving computational problems - are the foundation of computer programming. Mastering the most important algorithms and learning to recognize where they should be applied are required skills for any developer. Algorithms in Motion introduces you to the world of algorithms and how to use them as effectively as possible through high-quality video-based lessons and real-world examples, so you can put what you learn into practice. Based on the best-selling book Grokking Algorithms, this video course brings classic algorithms to life!
About the subjectAn algorithm is a repeatable procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. This engaging course makes it easy to learn and use the most important algorithms effectively.
About the videoAlgorithms in Motion teaches you how to apply common algorithms to the practical problems you face every day as a programmer. Following the expert guidance of liveVideo instructor Beau Carnes, you'll start with the basics, including Big O notation, fundamental data structures, and recursion. Then, you'll explore problem-solving techniques, that will empower you to see the algorithm you need in the task you're trying to accomplish. Finally, you'll finish the course by applying more advanced algorithms, such as hash tables, graph algorithms, and K-nearest.
Prerequisites
This easy-to-follow video course is perfect for self-taught programmers, engineers, or anyone who wants to brush up on classic algorithms.
Inside:- Search, sort, and graph algorithms
- Breadth-first search
- Performance concerns
- Implementing algorithms in Python
Grokking Algorithms by Adit Bhargava is available at manning.com in pBook, eBook, and liveBook formats.
Great way to quickly recap the most common algorithms.
Jonathan Wood, Software Consultant, Wintellect
Explains the fundamentals of some fairly complex computer science in a way that makes sense to anyone.
Derek Hampton, Senior Developer, Advanced Retail Ltd
A gentle introduction to the traditional computer science topics of data structures and algorithms in a way that is not intimidating to approach.
Ryan Burrows, Senior Software Developer, Rooster Park Consulting
Table of Contents
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Unit 1 - INTRODUCTION TO ALGORITHMS
- Introduction 00:07:55
- Binary Search 00:07:41
- Big O Notation 00:14:24
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Unit 2 - SELECTION SORT
- Arrays and Linked Lists 00:11:37
- Selection Sort 00:06:36
- Unit 3 - RECURSION
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Unit 4 - QUICKSORT
- Divide and Conquer 00:10:23
- Quicksort 00:07:05
- Big O Notation Revisited 00:07:40
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Unit 5 - HASH TABLES
- Hash Functions 00:07:27
- Use Cases 00:08:37
- Collisions 00:03:59
- Performance 00:06:26
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Unit 6 - BREADTH-FIRST SEARCH
- Graph Introduction 00:09:43
- Implementing the graph 00:11:15
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Unit 7 - DIJKSTRA'S ALGORITHM
- Working with Dijkstra's algorithm 00:06:38
- Trading for a piano 00:09:50
- Implementing Dijkstra's algorithm 00:09:18
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Unit 8 - GREEDY ALGORITHMS
- Greedy Algorithm Examples 00:12:46
- NP Complete Problems 00:08:55
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Unit 9 - DYNAMIC PROGRAMMING
- The Knapsack Problem 00:09:43
- The Knapsack Problem FAQ 00:08:17
- Longest Common Substring 00:09:42
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Unit 10 - K-NEAREST NEIGHBORS
- Classifying Oranges vs Grapefruits 00:06:24
- Regression and Features 00:05:15
- Introduction to Machine Learning 00:04:54
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Unit 11 - WHERE TO GO NEXT
- Trees 00:02:49
- Inverted Indexes 00:00:59
- The Fourier Transform 00:01:33
- Parallel Algorithms 00:02:20
- MapReduce 00:03:14
- Bloom Filters and HyperLogLog 00:04:13
- SHA Algorithms 00:03:29
- Locality Sensitive Hashing 00:01:28
- Diffie Hellman Key Exchange 00:02:39
- Linear Programming 00:02:21