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Data Structure and Algorithms

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Video Description

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.


In this Learning Data Structures and Algorithms training course, expert author Rod Stephens will teach you how to analyze and implement common algorithms used. This course is designed for the absolute beginner, meaning no previous programming experience is required.

You will start by learning about the complexity theory and then jump into learning about numerical algorithms, including randomizing arrays, prime factorization, and numerical integration. From there, Rod will teach you about linked lists, such as singly linked lists, sorted, and doubly linked lists. This video tutorial also covers arrays, stacks and queues, and sorting. You will also learn about searching, hash tables, recursion, and backtracking algorithms. Finally, you will cover trees, balanced trees.

Expert author Robert Sedgewick start with 1d and 2d range searching, where the goal is to find all points in a given 1d or 2d interval. To accomplish this, we consider kd-trees, a natural generalization of BSTs when the keys are points in the plane (or higher dimensions). We also consider intersection problems, where the goal is to find all intersections among a set of line segments or rectangles.

We begin by describing the desirable properties of hash function and how to implement them in Java, including a fundamental tenet known as the uniform hashing assumption that underlies the potential success of a hashing application. Then, we consider two strategies for implementing hash tables—separate chaining and linear probing. Both strategies yield constant-time performance for search and insert under the uniform hashing assumption. Finally you will focuses on graph, minimum spanning trees,shortest paths, maximum flow and minimum cut.

Once you have completed this computer based training course, you will be fully capable of analyzing and implementing algorithms, as well as be able to select the best algorithm for various situations. Working files are included, allowing you to follow along with the author throughout the lessons


Course Curriculum

Chapter 1.Introduction
1.Introduction And Course Overview 00:04:00
Chapter 2.Complexity Theory
2.Complexity Theory 00:03:56
3.Big O Notation 00:07:02
4.Typical Runtime Functions 00:04:37
5.Comparing Runtime Functions 00:05:27
6.P And NP 00:04:04
Complexity Theory_Working files 00:00:00
Chapter 3.Numerical Algorithms
7.Random Numbers 00:02:19
8.Linear Congruential Generators 00:05:04
9.Randomizing Arrays – Part 1 00:03:47
10.Randomizing Arrays – Part 2 00:04:31
11.GCD 00:04:09
12.LCM 00:03:28
13.Prime Factorization – Part 1 00:04:59
14.Prime Factorization – Part 2 00:02:43
15.Finding Primes 00:03:24
16.Testing Primality 00:03:45
17.Numerical Integration 00:05:11
Numerical Algorithms_Working files 00:00:00
Chapter 4.Linked Lists
18.Singly Linked Lists – Part 1 00:06:48
19.Singly Linked Lists – Part 2 00:02:22
20.Sorted Linked Lists 00:03:22
21.Sorting With Linked Lists 00:04:07
22.Doubly Linked Lists 00:03:51
Linked Lists_Working files 00:00:00
23.One-Dimensional Arrays 00:05:10
24.Triangular Arrays – Part 1 00:04:13
25.Triangular Arrays – Part 2 00:03:17
26.Sparse Arrays – Part 1 00:05:27
27.Sparse Arrays – Part 2 00:03:19
Arrays_Working files 00:00:00
Chapter 6.Stacks Queues
28.Stacks 00:02:32
29.Stack Algorithms 00:03:26
30.Double Stacks 00:02:08
31.Queues 00:05:49
Stacks Queues_Working files 00:00:00
Chapter 7.Sorting
32.Sorting Algorithms 00:03:03
33.Insertionsort 00:06:27
34.Selectionsort 00:04:46
35.Quicksort – Part 1 00:05:40
36.Quicksort – Part 2 00:07:55
37.Heapsort – Part 1 00:06:17
38.Heapsort – Part 2 00:05:21
39.Heapsort – Part 3 00:05:39
40.Mergesort – Part 1 00:03:55
41.Mergesort – Part 2 00:03:41
42.Bubblesort – Part 1 00:04:51
43.Bubblesort – Part 2 00:04:18
44.Countingsort – Part 1 00:04:45
45.Countingsort – Part 2 00:03:35
46.Sorting Summary 00:02:51
Sorting_Working files 00:00:00
Chapter 8.Searching
47.Linear Search 00:02:11
48.Binary Search 00:05:15
49.Interpolation Search 00:05:27
Searching_Working files 00:00:00
Chapter 9.Hash Tables
50.Hash Tables 00:04:32
51.Chaining 00:05:23
52.Open Addressing – Basics 00:07:25
53.Open Addressing – Linear Probing 00:04:48
54.Open Addressing – Quadratic Probing 00:04:22
55.Open Addressing – Double Hashing 00:05:55
Hash Tables_Working files 00:00:00
Chapter 10.Recursion
56.Recursion Basics 00:05:37
57.Fibonacci Numbers 00:06:08
58.Tower Of Hanoi 00:06:08
59.Koch Curves 00:04:32
60.Hilbert Curves 00:04:32
61.Gaskets 00:04:52
62.Removing Tail Recursion 00:03:58
63.Removing Recursion With Stacks 00:03:56
64.Fixing Fibonacci 00:07:25
65.Selections 00:04:15
66.Permutations 00:04:12
Recursion_Working files 00:00:00
Chapter 11.BackTracking Algorithms
67.Backtracking 00:06:03
68.The Eight Queens Problem – Part 1 00:06:00
69.The Eight Queens Problem – Part 2 00:04:03
70.The Eight Queens Problem – Part 3 00:03:48
71.The Knights Tour 00:04:20
BackTracking Algorithms_Working files 00:00:00
Chapter 12.Trees
72.Tree Terms 00:05:06
73.Binary Tree Properties 00:06:25
74.Traversals – Preorder 00:03:54
75.Traversals – Postorder 00:02:57
76.Traversals – Inorder 00:02:47
77.Traversals – Breadth-First 00:02:57
78.Building Sorted Trees 00:03:56
79.Editing Sorted Trees 00:04:36
Trees_Working files 00:00:00
Chapter 13.Balance Trees
80.Search Trees – Algorithms 24-part Lecture Series 00:16:55
81.Red-Black BSTs – Algorithms 24-part Lecture Series 00:35:30
82.B-Trees – Algorithms 24-part Lecture Series 00:10:37
Balance Trees_Working files 00:00:00
Chapter 14.Geometric Applications Of BST
83.Range Search – Algorithms 24-part Lecture Series 00:08:52
84.Line Segment Intersection – Algorithms 24-part Lecture Series 00:05:46
85.Kd-Trees – Algorithms 24-part Lecture Series 00:29:07
86.Interval Search Trees – Algorithms 24-part Lecture Series 00:13:47
87.Rectangle Intersection – Algorithms 24-part Lecture Series 00:08:11
Geometric Applications Of BST_Working files 00:00:00
Chapter 15.Hash Tables
88.Hash Functions – Algorithms 24-part Lecture Series 00:18:14
89.Separate Chaining – Algorithms 24-part Lecture Series 00:07:28
90.Context 00:10:10
91.Linear Probing – Algorithms 24-part Lecture Series 00:14:37
92.Sets 00:05:04
93.Dictionary Clients 00:05:39
94.Indexing Clients 00:07:52
95.Sparse Vectors 00:07:41
Hash Tables_Working files 00:00:00
Chapter 16.Undirected Graphs
96.Introduction To Graphs 00:09:32
97.Graph API 00:14:47
98.Depth First 00:26:22
99.Breadth First 00:13:34
100.Connected Components 00:18:56
101.Graph Challenges 00:14:29
Chapter 17.Directed Graphs
102.Introduction Directed Graphs 00:08:30
103.Digraph API 00:04:56
104.Digraph Search 00:20:56
105.Topological Search 00:12:54
106.Strong Components 00:20:22
Chapter 18.Minimum Spanning Trees
107.Introduction to MSTs – Algorithms 24-part Lecture Series 00:04:04
108.Greedy Algorithm 00:12:56
109.Edge Weighted Graph API 00:11:15
110.Kruskal’s Algorithm 00:12:28
111.Prims Algorithm 00:33:15
112.MST Context – Algorithms 24-part Lecture Series 00:10:34
Chapter 19.Shortest Paths
113.Shortest Paths Introduction 00:10:51
114.Shortest Path Properties – Algorithms 24-part Lecture Series 00:14:46
115.Dijkstra Algorithm 00:18:58
116.Edge Weighted DAG 00:19:23
117.Negative Weights 00:21:01
Chapter 20.Maximum Flow and Minimun Cut
118.Introduction to Maxflow – Algorithms 24-part Lecture Series 00:10:33
119.Ford Fulkerson algorithm 00:06:32
120.Maxflow-Mincut Theorem – Algorithms 24-part Lecture Series 00:09:39
121.Running Time analysis 00:08:49
122.Java Implementation 00:14:29
123.Maximum applications 00:22:20

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