Algorithms in Java: Live problem solving & Design Techniques

19h 41m 26s
English
Paid
July 8, 2024

Algorithm Design Techniques: Live problem-solving in Java. Algorithms are everywhere. One great algorithm applied sensibly can result in a System like GOOGLE! Completer scientists have worked from 100s of years and derived some of the techniques that can be applied to write and design algorithms. So Why to reinvent the wheel ?? Let’s go through some of the most famous algorithm design techniques in this course.

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Once you will come to know these design techniques It will become very easy for you to approach a problem by identifying which technique to apply to solve that correctly and efficiently.

0. Complexity analysis

1. Recursion is the base of any algorithm design

2. Backtracking

3. Divide and Conquer

4. Greedy algorithms

5. Dynamic programming

And WE WILL WRITE THE CODE LINE BY LINE IN JAVA !!

By the end of this course -

    1. You will understand how to design algorithms

    2. A lot of coding practice and design live problems in Java

    3. Algorithm Complexity analysis

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# Title Duration
1 Course Introduction 04:08
2 Introduction to Algorithms 03:50
3 Section Introduction 01:15
4 Complexity Analysis 1 07:42
5 Complexity Analysis 2 14:04
6 Section Summary 01:14
7 Section Introduction 00:38
8 Recurrence Relation 05:39
9 Solving Recurrence Relation 11:19
10 Master's Theorem 05:36
11 Section Summary 00:31
12 Section Introduction 01:57
13 Recursion 07:01
14 Identification 06:10
15 Approaching 04:36
16 Problem 01 : FindingSubsequences - Logic 04:07
17 Problem 01 : FindingSubsequences - Live Code Java 05:40
18 Problem 01 : FindingSubsequences - Complexity Analysis 02:21
19 Problem 02: Tower of Hanoi - Logic 05:39
20 Problem 02 : Tower of Hanoi - Live Code Java 04:49
21 Problem 02 : Tower of Hanoi - Complexity Analysis 11:11
22 Problem 03 : 7.Array Product Sum - Logic 04:32
23 Problem 03 : 7.Array Product Sum - Live Code Java 05:00
24 Problem 03 : Array Product Sum - Complexity Analysis 01:08
25 Problem 04 : Binary Subtree - Logic 06:23
26 Problem 04 : Binary Subtree - Live Code Java 08:25
27 Problem 04 : Binary Subtree - Complexity Analysis 00:58
28 Why and Why not Recursion 01:19
29 Types Of Recursion 04:02
30 Tail Recursion 05:19
31 Section Summary 01:01
32 Section Introduction 01:28
33 Introduction to Backtracking 01:45
34 Identify Backtracking 03:04
35 Approching the Solution 09:37
36 Problem 01 : Rat In Maze - Logic 08:41
37 Problem 01 : Rat In Maze - Code 08:45
38 Problem 01 : Rat In Maze - Complexity Analysis 01:20
39 Problem 02 : NQueen - Logic 08:44
40 Problem 02 : NQueen - Live Code in Java 08:10
41 Problem 02 : NQueen - Complexity Analysis 02:09
42 Problem 03 : Knights Tour Problem - Logic 05:02
43 Problem 03 : Knights Tour Problem - Live Code in Java 07:01
44 Problem 03 : Knight Tour Problem - Complexity Analysis 00:52
45 Problem 04 : Boggle | Word Search - Logic 05:49
46 Problem 04 : Boggle | Word Search - Live Code in Java 07:44
47 Problem 04 : Boggle | Word Search - Complexity Analysis 00:53
48 Section Summary 01:10
49 Section Introduction 00:45
50 Introduction To Divide And Conquer 03:16
51 Identification and Approaching 03:33
52 Problem 01 : MergeSort - Logic 09:34
53 Problem 01 : MergeSort - Live Java Code 08:43
54 Problem 01 : MergeSort - Complexity Analysis 04:22
55 Problem 02 : QuickSort - Logic 11:06
56 Problem 02 : QuickSort - Live Java Code 06:13
57 Problem 02 : QuickSort - Complexity Analysis 02:30
58 Problem 03 : Median Of Medians - Logic 09:01
59 Problem 03 : Median Of Medians - Live Java Code 14:53
60 Section Summary 00:43
61 Section Introduction 00:57
62 Introduction to Greedy 05:23
63 Identification & Approaching the Solution 03:08
64 Problem 01 : Fractional Knapsack - Logic 06:24
65 Problem 01 : Fractional Knapsack - Live Code Java 09:37
66 Problem 01 : Fractional Knapsack - Complexity Analysis 00:58
67 Problem 02 : IntervalScheduling - Logic 03:12
68 Problem 02 : IntervalScheduling - Live Code Java 07:48
69 Problem 02 : IntervalScheduling - Complexity Analysis 01:39
70 Problem 03 : Huffman Code - Logic 12:27
71 Problem 03 : Huffman Code - Live Code Java 19:04
72 Problem 03 : Huffman Code - Complexity Analysis 01:50
73 Problem 04 : Dijkstra - Logic 09:22
74 Problem 04 : Dijkstra Logic - Live Code 08:59
75 Problem 04 : Dijkstra - Complexity Analysis 01:02
76 Summary 00:43
77 Section Introduction 02:16
78 Introduction to Dynamic Programming 05:25
79 Identification 01:20
80 Compare DP D&C and Greedy 03:15
81 Approaching the Solution 03:44
82 Example 01 : Staircase Problem Theory & Live Code 15:42
83 Example 01 : Staircase Problem Complexity Analysis 03:05
84 Example 02 - 0/1 Knapsack Theory & Live code 26:36
85 Example 02 - 0/1 Knapsack Complexity Analysis 02:46
86 Example 03 - Coin Change Problem Theory and Code 25:35
87 Example 03 - Coin Change Problem Complexity Analysis 03:57
88 Example 04 : Longest Decreasing Subsequence Explanation And Code 27:55
89 Example 04 : Longest Decreasing Subsequence | Complexity Analysis 01:37
90 Example 05 : Levenshtein problem 23:29
91 Example 05 : Levenshtein Complexity Analysis 01:54
92 Example 06 : Rod Cutting 18:16
93 Example 06 : Rod Cutting - Complexity Analysis 01:42
94 Example 07 : Matrix Chain Multiplication 26:10
95 Example 07 : Matrix Chain Multiplication | Complexity Analysis 02:31
96 Summary 00:44
97 Kadane's Algo 07:40
98 Kadane's Algo Live Code Java 03:35
99 Kadane's Algo Complexity Analysis 00:34
100 BellmanFord's Algo 06:47
101 BellmanFord's Algo Live Code Java 11:20
102 BellmanFord's Algo Complexity Analysis 00:52
103 Topological Sort : Kahn's Algo 06:32
104 Topological Sort Live Code Java 13:54
105 Topological Sort Complexity Analysis 01:48
106 Edmond's Karp/Ford-Fulkerson Algorithm 26:35
107 Ford-Fulkerson Algorithm - Edmond's Karp Implementation 20:16
108 Tree Overview 23:28
109 Identification 02:02
110 Approaching Tree Problems 04:36
111 Problem 1: Sum Tree - Logic 09:29
112 Problem 1: Sum Tree - Live Code 04:55
113 Problem 2: Invert Binary Tree - Logic 02:20
114 Problem 2: Invert Binary Tree - Live Code 03:53
115 Problem 3: Binary Search Tree - Logic 11:46
116 Problem 3: Binary Search Tree - Live Code 16:19
117 Problem 4: Binary Tree from InOrder & LevelOrder - Logic 03:47
118 Problem 4: Binary Tree from InOrder & LevelOrder - Live Code 07:50
119 Graphs - In Real World 04:57
120 Graphs - Overview 11:54
121 Identification of Problem 03:54
122 Approaching the Problem 09:13
123 Mind-Map 02:36
124 Type - Graph Traversal 02:29
125 Depth First Search Traversal 06:18
126 DFS - Implementation (Recursive) 07:07
127 DFS - Implementation (Iterative) 04:50
128 Breadth First Search Traversal 03:27
129 BFS - Implementation 04:59
130 Type - Minimum Spanning Tree 05:30
131 Prim's Algorithm 09:29
132 Prim's Algorithm - Implementation 07:34
133 Kruskal's Algorithm 03:56
134 Union-Find Algorithm 08:10
135 Kruskal's Algorithm - Implementation 13:15
136 Type - Shortest Path 01:17
137 Dijkstra's Algorithm 09:22
138 Dijkstra's Algorithm - Implementation 08:59
139 BellmanFord's Algo 06:47
140 BellmanFord's Algo Live Code 11:20
141 Floyd Warshall Algorithm 06:46
142 Floyd-Warshall Algorithm - Implementation 05:47
143 Johnson's Algorithm 15:41
144 Johnson's Algorithm - Implementation 20:23
145 Type - Network Flow 04:40
146 Ford-Fulkerson Algorithm 26:35
147 Ford-Fulkerson Algorithm - Edmond's Karp Implementation 20:16
148 Max-Flow Min-Cut Theorem 05:46
149 Type - Strongly Connected Components 02:50
150 Tarjan's Algorithm 09:55
151 Tarjan's Algorithm - Implementation 12:25
152 Kosaraju's Algorithm 06:07
153 Kosaraju's Algorithm - Implementation 11:01
154 Section Introduction 01:20
155 Single Dimension Arrays 13:14
156 Multi Dimension Arrays 12:43
157 Declaration , Initialisation & Creation 19:04
158 Playing With Arrays Syntax Java 10:49
159 Traversing Arrays,Length of Array Java 13:35
160 Types of Array - based on elements it holds 11:53
161 Reassigning Array Objects to Array References 13:17
162 Anonymous Arrays 03:50
163 Arrays-Summay 00:49

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