Java Data Structures and Algorithms Masterclass

44h 58m 57s
English
Paid
July 8, 2024

Welcome to the Java Data Structures and Algorithms Masterclass, the most modern, and the most complete Data Structures and Algorithms in Java course on the internet. At 45+ hours, this is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms in Java. 

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You will see 100+ Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft and how to face Interviews with comprehensive visual explanatory video materials which will bring you closer towards landing the tech job of your dreams!

Learning Java is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Data Structures and how algorithms are implemented in high level programming language.

We'll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.

After finishing this course, you will be able to:

  • Learn basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.
  • Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications
  • Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets
  • Learn how to apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.

Why this course is so special and different from any other resource available online?

  • This course will take you from very beginning to a very complex and advanced topics in understanding Data Structures and Algorithms!
  • You will get video lectures explaining concepts clearly with comprehensive visual explanations throughout the course.
  • You will also see Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft.
  • I cover everything you need to know about technical interview process!

So whether you are interested in learning the top programming language in the world in-depth and interested in learning the fundamental Algorithms, Data Structures and performance analysis that make up the core foundational skillset of every accomplished programmer/designer or software architect and is excited to ace your next technical interview this is the course for you!

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# Title Duration
1 Curriculum Walkthrough 08:22
2 What is a data structure? 03:27
3 What is an algorithm? 03:54
4 Why are Data Structures and Algorithms important? 03:41
5 Types of Data Structures 03:23
6 Types of Algorithms 04:01
7 Goals : what you will learn by the end of this section 01:06
8 What is Recursion? 05:01
9 Why do we need Recursion? 03:22
10 The Logic Behind Recursion 09:16
11 Recursive vs Iterative Solution 04:14
12 When to Use/Avoid Recursion? 06:22
13 How to Write Recursion in 3 Steps? 13:43
14 Fibonacci Series using Recursion 09:38
15 Question 1 - Sum of Digits 08:51
16 Question 2 - Power 05:56
17 Question 3 - GCD 06:41
18 Question 4 - Decimal to Binary 08:17
19 What is Big O? 03:21
20 Big O Notations (Big O, Big Omega, Big Theta) 08:03
21 Most Common Time Complexities 10:08
22 Space Complexity 02:42
23 Drop Constants and Non Dominant Terms 03:56
24 Addition vs Multiplication 02:28
25 How to Measure the Code using Big O? 04:49
26 How to Measure Recursive Algorithm? 07:20
27 How to Measure Recursive Algorithm with Multiple Calls? 04:08
28 Question 1 - Time Complexity of Method that returns Sum and Product of Array 05:47
29 Question 2 - Time Complexity of Print Pairs Method 05:51
30 Question 3 - Time Complexity of Print Unordered Pairs Method 04:32
31 Question 4 - Find Time Complexity for Given Method 02:15
32 Question 5 - Find Time Complexity for Given Method 01:36
33 Question 6 - Time Complexity of Reverse Array Function 06:05
34 Question 7 - Equivalent to O(N) 03:24
35 Question 8 - Time Complexity of Factorial 02:52
36 Question 9 - Time Complexity of Fibonacci 02:56
37 Question 10 - Time Complexity Powers Of 2 03:00
38 What is an Array? 07:58
39 Types of Arrays 06:52
40 Arrays in Memory 03:53
41 Create an Array 09:06
42 Insertion in Array 11:37
43 Accessing Elements in Array 05:13
44 Array Traversal 07:28
45 Search for Array Element 07:53
46 Delete Array Element 05:58
47 Time and Space Complexity of 1D Arrays 04:21
48 Create Two Dimensional Array 11:06
49 Insertion - Two Dimensional Array 10:39
50 Accessing Two Dimensional Array Element 07:17
51 Traverse Two Dimensional Array 07:22
52 Searching Two Dimensional Array 08:15
53 Delete Two Dimensional Array Element 06:38
54 Time and Space Complexity of 2D Arrays 04:07
55 When to Use/Avoid Arrays 02:38
56 Goals - what you will make by the end of this section 02:52
57 Calculate Average Temperature 07:09
58 Find the Days Above Average Temperature 06:44
59 Section Goals 00:43
60 Solution - Missing Number 06:57
61 Solution - Pairs 09:12
62 Solution - Finding a Number in an Array 05:27
63 Solution - Max Product of Two Integers 06:06
64 Solution - IsUnique / Contains Duplicate - LeetCode 217 05:16
65 Solution - Permutation 08:35
66 Rotate Matrix / Image - LeetCode 48 12:30
67 What is a Linked List? 05:58
68 Linked List vs Array 03:50
69 Types of Linked List 10:54
70 Linked List in the Memory 04:02
71 Creation of Singly Linked List 09:54
72 Insertion in Singly Linked List in Memory 03:54
73 Insertion Algorithm in Singly Linked List 08:03
74 Insertion Method in Singly Linked List 14:56
75 Traversal of Singly Linked List 09:49
76 Searching in Singly Linked List 08:50
77 Deletion of a Node from Singly Linked List 09:38
78 Deletion Method in Singly Linked List 15:39
79 Deletion of Entire Singly Linked List 05:57
80 Time and Space Complexity of Singly Linked List 04:06
81 Create Circular Singly Linked List 12:59
82 Insertion in Circular Singly Linked List 07:31
83 Insertion Algorithm in Circular Singly Linked List 04:49
84 Insertion Method Circular Singly Linked List 12:00
85 Traversal of Circular Singly Linked List 09:58
86 Searching a Node in Circular Singly Linked List 09:49
87 Deletion of a Node from Circular Singly List 08:39
88 Deletion Algorithm in Circular Singly Linked List 05:20
89 Deletion Method in Circular Singly Linked List 11:21
90 Delete Entire Circular Singly Linked List 06:32
91 Time and Space Complexity of Circular Singly Linked List 05:33
92 Create Doubly Linked List 13:46
93 Insertion Doubly Linked List 09:55
94 Insertion Algorithm Doubly Linked List 06:30
95 Insertion Method Doubly Linked List 14:55
96 Traversal of Doubly Linked List 08:36
97 Reverse Traversal of Doubly Linked List 08:22
98 Searching for a Node in Doubly Linked List 08:56
99 Deletion of a Node in Doubly Linked List 08:34
100 Deletion Algorithm Doubly Linked List 06:09
101 Deletion Method in Doubly Linked List 13:45
102 Delete Entire Doubly Linked List 07:25
103 Time and Space Complexity of Doubly Linked List 05:28
104 Create Doubly Linked List 12:22
105 Insertion Circular Doubly Linked List 10:30
106 Insertion Algorithm Circular Doubly Linked List 06:59
107 Insertion Method Circular Doubly Linked List 13:55
108 Traversal of Circular Doubly Linked List 08:32
109 Reverse Traversal of Circular Doubly Linked List 08:18
110 Search for a Node in Circular Doubly Linked List 09:00
111 Deletion in Circular Doubly Linked List 10:54
112 Deletion Algorithm in Circular Doubly Linked List 06:48
113 Deletion Method in Circular Doubly Linked List 11:52
114 Delete Entire Circular Doubly Linked List 07:41
115 Time and Space Complexity of Circular Doubly Linked List 04:35
116 Time Complexity of Array vs Linked List 07:13
117 Linked List Class 10:19
118 Solution - Remove Dups 10:52
119 Solution - Return Nth to Last 09:20
120 Solution - Partition 09:37
121 Solution - Sum Lists 10:52
122 Solution - Intersection 13:21
123 What and Why of Stack? 05:28
124 Stack Operations 06:33
125 Stack using Array vs Linked List 01:33
126 Stack Operations using Array (Create, isEmpty, isFull) 08:23
127 Stack Operations using Array (Push, Pop, Peek, Delete) 12:41
128 Time and Space Complexity of Stack using Array 02:49
129 Stack Operations using Linked List 06:47
130 Stack methods - Push , Pop, Peek, Delete and isEmpty using Linked List 18:12
131 Time and Space Complexity of Stack using Linked List 03:22
132 When to Use/Avoid Stack 02:15
133 What is a Queue? 06:33
134 Linear Queue Operations using Array 00:00
135 Create, isFull, isEmpty and enQueue methods using Linear Queue Array 14:45
136 Dequeue, Peek and Delete Methods using Linear Queue Array 10:46
137 Time and Space Complexity of Linear Queue using Array 03:49
138 Why Circular Queue? 04:37
139 Circular Queue Operations using Array 08:00
140 Create, Enqueue, isFull and isEmpty Methods in Circular Queue using Array 18:20
141 Dequeue, Peek and Delete Methods in Circular Queue using Array 12:22
142 Time and Space Complexity of Circular Queue using Array 03:56
143 Queue Operations using Linked List 07:54
144 Create, Enqueue and isEmpty Methods in Queue using Linked List 10:45
145 Dequeue, Peek and Delete Methods in Queue using Linked List 10:28
146 Time and Space Complexity of Queue using Linked List 03:04
147 Array vs Linked List Implementation 02:28
148 When to Use/Avoid Queue? 01:57
149 Goals 01:04
150 Solution - Three in One 23:49
151 Solution - Stack Minimum 12:48
152 Solution Part 1 - Stack of Plates 14:29
153 Solution Part 2 - Stack of Plates 10:57
154 Solution Part 3 - Follow UP 08:11
155 Solution - Queue via Stacks 11:50
156 Solution - Animal Shelter 24:49
157 What is a Tree? 07:26
158 Why Tree? 02:41
159 Tree Terminology 05:17
160 Creating a Basic Tree in Java 09:44
161 What is A Binary Tree? 03:10
162 Types of Binary Tree 03:50
163 Binary Tree Representation 07:35
164 Create Binary Tree using Linked List 06:10
165 PreOrder Traversal in Binary Tree using Linked List 12:02
166 InOrder Traversal in Binary Tree using Linked List 08:49
167 PostOrder Traversal in Binary Tree using Linked List 07:03
168 LevelOrder Traversal in Binary Tree using Linked List 08:48
169 Search Method in Binary Tree (Linked List) 09:31
170 Insert Method in Binary Tree (Linked List) 12:37
171 Delete a Node in Binary Tree (Linked List) 20:30
172 Delet Entire Binary Tree (Linked List) 02:40
173 Create Binary Tree (Array) 07:28
174 Insert Method Binary Tree (Array) 07:57
175 PreOrder Traversal Binary Tree (Array) 07:26
176 InOrder Traversal Binary Tree (Array) 06:25
177 PostOrder Traversal Binary Tree (Array) 05:24
178 levelOrder Traversal Binary Tree (Array) 05:46
179 Search Method Binary Tree (Array) 07:07
180 Delete a Node Binary Tree (Array) 06:33
181 Delete Binary Tree (Array) 03:07
182 Array vs Linked List in Binary Tree Implementation 06:01
183 What is a Binary Search Tree? Why do we need it? 03:29
184 Create Binary Search Tree 04:38
185 Insert a Node to Binary Search Tree 12:07
186 PreOrder Traversal Binary Search Tree 04:45
187 InOrder Traversal Binary Search Tree 04:10
188 PostOrder Traversal Binary Search Tree 03:41
189 Level Order Traversal Binary Search Tree 05:12
190 Search in Binary Search Tree 07:42
191 Delete a Node in Binary Search Tree 17:19
192 Delete BST 02:51
193 Time and Space Complexity of BST 03:37
194 What is an AVL Tree? 07:24
195 Why Do We Need AVL Tree? 04:00
196 Common Operations on AVL Tree 12:19
197 Insert a Node in AVL (Left Left Condition) 13:33
198 Insert a Node in AVL (Left Right Condition) 08:31
199 Insert a Node in AVL (Right Right Condition) 08:01
200 Insert a Node in AVL (Right Left Condition) 06:37
201 Insert a Node in AVL (All Together) 14:27
202 Insert a Node in AVL (Method in Practice) 21:06
203 Delete a Node from AVL (LL, LR, RR, RR) 10:05
204 Delete a Node from ALL (All Together) 07:05
205 Delete a Node from AVL (Method in practice) 13:42
206 Delete Entire AVL Tree 02:11
207 Time and Space Complexity of AVL 03:03
208 Binary Search Tree vs AVL 02:57
209 What is Binary Heap? Why do we need Binary Heap? 07:40
210 Common Operations on Binary Heap 18:48
211 Insert a Node in Binary Heap 14:46
212 Extract a Node from Binary Heap 19:20
213 Delete Entire Binary Heap 02:46
214 Time and Space Complexity of Binary Heap 05:31
215 What is a Trie? Why we need Trie? 10:58
216 Common Operations on a Trie (Creation) 06:24
217 Insert a String in Trie 14:42
218 Search for a String in Trie 13:01
219 Delete a String from Trie 16:58
220 Practical Uses of Trie 02:15
221 What is Hashing? Why we need it? 05:38
222 Hashing Terminology 04:46
223 Hash Functions 09:47
224 Types of Collision Resolution Techniques - Direct Chaining (Insert) 16:52
225 Direct Chaining Implementation - (Search, Delete) 07:29
226 Hash Table is Full 04:41
227 Collision Resolution Technique - Linear Probing (Insert) 17:45
228 Collision Resolution Technique - Linear Probing (Search, Delete) 08:39
229 Collision Resolution Technique - Open Addressing : Quadratic Probing 09:12
230 Collision Resolution Technique - Open Addressing : Double Hashing 13:50
231 Pros and Cons of Resolution Techniques 05:11
232 Practical Use of Hashing 04:18
233 Hashing vs Other DS 02:10
234 What is Sorting? 03:00
235 Types of Sorting 06:52
236 Sorting Terminology 05:10
237 Bubble Sort 15:45
238 Selection Sort 11:35
239 Insertion Sort 13:51
240 Bucket Sort 21:11
241 Merge Sort 15:49
242 Quick Sort 22:11
243 Heap Sort 18:21
244 Comparison of Sorting Algorithms 01:30
245 Introduction To Search Algorithms 01:45
246 Linear Search 04:01
247 Linear Search in Java 07:12
248 Binary Search 03:04
249 Binary Search in Java 13:04
250 Time Complexity of Binary Search 05:15
251 What you will learn 01:41
252 What is a Graph? Why do we need Graph 04:50
253 Graph Terminology 05:06
254 Types of Graph 05:47
255 Graph Representation 09:55
256 Graph in Java using Adjacency Matrix 12:57
257 Graph in Java using Adjacency List 09:51
258 Breadth First Search Algorithm (BFS) 10:37
259 Breadth First Search Algorithm (BFS) in Java - Adjacency Matrix 11:22
260 Breadth First Search Algorithm (BFS) in Java - Adjacency List 06:30
261 Time Complexity of Breadth First Search (BFS) Algorithm 03:25
262 Depth First Search (DFS) Algorithm 07:23
263 Depth First Search (DFS) Algorithm in Java - Adjacency List 06:35
264 Depth First Search (DFS) Algorithm in Java - Adjacency Matrix 06:35
265 Time Complexity of Depth First Search (DFS) Algorithm 03:08
266 BFS Traversal vs DFS Traversal 04:33
267 What is Topological Sort? 02:57
268 Topological Sort Algorithm 09:14
269 Topological Sort using Adjacency List 10:56
270 Topological Sort using Adjacency Matrix 07:24
271 Time and Space Complexity of Topological Sort 03:14
272 What is Single Source Shortest Path Problem? 04:46
273 Breadth First Search (BFS) for Single Source Shortest Path Problem (SSSPP) 07:04
274 BFS for SSSPP in Java using Adjacency List 11:09
275 BFS for SSSPP in Java using Adjacency Matrix 07:25
276 Time and Space Complexity of BFS for SSSPP 02:51
277 Why does BFS not work with Weighted Graph? 03:38
278 Why does DFS not work for SSSP? 02:16
279 Dijkstra's Algorithm for SSSPP 06:23
280 Dijkstra's Algorithm in Java - 1 12:36
281 Dijkstra's Algorithm in Java - 2 08:47
282 Dijkstra's Algorithm with Negative Cycle 03:47
283 Bellman Ford Algorithm for SSSPP 10:56
284 Bellman Ford Algorithm with Negative Cycle 05:19
285 Why Bellman Ford runs V-1 times? 04:21
286 Bellman Ford Algorithm Implementation in Java 10:46
287 BFS vs Dijkstra vs Bellman Ford 03:38
288 What is All Pairs Shortest Path Problem? 04:24
289 Dry Run for All Pairs Shortest Path Problem 04:25
290 Floyd Warshall Algorithm 09:11
291 Why Floyd Warshall Algorithm? 04:50
292 Floyd Warshall with Negative Cycle 02:34
293 Floyd Warshall in Java 12:28
294 BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall Algorithms 02:43
295 What is Minimum Spanning Tree? 04:34
296 What is Disjoint Set? 02:56
297 Disjoint Set in Java 11:51
298 Kruskal Algorithm 09:12
299 Kruskal Algorithm in Java 15:46
300 Prim's Algorithm 05:42
301 Prim's Algorithm in Java 09:59
302 Kruskal vs Prim's Algorithms 03:35
303 Introduction 00:40
304 Solution to Route Between Nodes 10:52
305 What is Greedy Algorithm? 05:37
306 Known Greedy Algorithms 08:31
307 Activity Selection Problem 05:37
308 Activity Selection Problem in Java 17:07
309 Coin Change Problem 04:27
310 Coin Change Problem in Java 08:11
311 Fractional Knapsack Problem 05:23
312 Fractional Knapsack Problem in Java 17:09
313 What is a Divide and Conquer Algorithm? 06:59
314 Common Divide and Conquer Algorithms 06:52
315 How to solve Fibonacci series using Divide and Conquer approach? 05:00
316 Number Factor 06:27
317 Number Factor in Java 05:45
318 House Robber 07:11
319 House Robber in Java 06:29
320 Convert One String to Another 06:16
321 Convert One String to Another in Java 07:56
322 Zero One Knapsack Problem 05:11
323 Zero One Knapsack Problem in Java 07:51
324 Longest Common Subsequence Problem 06:23
325 Longest Common Subsequence Problem in Java 07:04
326 Longest Palindromic Subsequence Problem 05:48
327 Longest Palindromic Subsequence Problem in Java 06:20
328 Minimum Cost to Reach Last Cell 05:03
329 Minimum Cost to Reach Last Cell in Java 05:07
330 Number of Paths To Reach The Last Cell with Given Cost 05:17
331 Number of Paths To Reach The Last Cell with Given Cost in Java 06:10
332 What is Dynamic Programming? (Overlapping property) 04:58
333 Where Does the Name of DP Come From? 02:09
334 Top Down with Memoization 11:28
335 Bottom Up with Tabulation 07:44
336 Top Down vs Bottom Up 04:18
337 Is Merge Sort Dynamic Programming? 04:31
338 Number Factor Problem using Dynamic Programming 12:27
339 Number Factor : Top Down and Bottom Up 08:34
340 House Robber Problem using Dynamic Programming 10:24
341 Convert one string to another using Dynamic Programming 05:30
342 Introduction 02:58
343 Step 1 - Understand the Problem 06:02
344 Step 2 - Examples 06:41
345 Step 3 - Break it Down 07:44
346 Step 4 - Solve or Simplify 10:56
347 Step 5 - Look Back and Refactor 07:34
348 What is Backtracking? 10:02
349 Backtracking vs Brute Force 04:35
350 N - Queens Problem 09:39

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