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Data Structure & Algorithms (DSA) for FAANG
ARTH Basic Linux
1. ARTH Introduction - DevOps | DSA | Task and Agenda (182:49)
2. Zenity | Espeak-ng | Date (184:28)
3. Firefox | Programs | Stty | Kill | Man | Yum configuration | Cowsay (197:05)
4.1 Python Menu | Tput | For loop | Functions (81:10)
5.1 Network | Network requirement | Spoofing | Asterisk | Exposed IP octet myth (75:00)
DSA Training
1. DSA introduction (97:44)
C++ | Python
50. C++ | STL | Auto detection of data type | Dynamic array using vector for-each loop | ADT | Various other functions (124:48)
51. C++ array operations | Linkedin list | Hashing and its technique (143:37)
52. Python Collision | Math function features (136:01)
HashTable
53. Abstract data types | Explain chaining | Sparse array | Resolving collision issues in Hash Table | Containers in C++ (123:49)
54. Difference between database and data structure | How to sort any directory | Data with ls cmd | How to do hashing with STL | What is call by reference (148:40)
55. About hashtable - traverse | Checking Table | Uses list functions. (141:35)
56. Hashing technique implements ADT | CRUD operation | Collision problem & resolve | About the Factor | Uniform data distribution | Best & worst case scenario time complexity (121:45)
57. Time complexity of hashtable | Searching in an array | Write syntax for creating a dictionary and hashtable in python | Function used to retrive keys and values | Use of 'in' operator (146:50)
Tree
59. Basics about Tree | Data structure | Terminologies used in Tree Data Structure such as (Leaf, root, sibling, etc) | Ancestor and Descendants | Implement a Tree DS | Binary Search Tree(BST) (132:47)
60. linear and nonlinear (difference, example) | Travers Binary Tree | Difference between Depth first traversal and Breadth first traversal | Traverse using pre-order (130:02)
61. Strict binary tree | Space and time complexity of pre-order & in-order traversal | In-order & post-order traversal (114:56)
62. Queue ( data structure, operations ) | Time complexity for enqueue and dequeue operation (134:18)
63. List some queue real-life applications | Types of queues | Complexity analysis of an enqueue and dequeue operation | Difference between no fixed capacity and fixed capacity queue | Explain OOM (141:52)
64. Condition for queue to be full & empty | Use of isFull() function | Use fixed capacity and not fixed array (space and time complexities) | Use cases of queue | Pass keyword | Enqueue function (136:07)
65. Name of STL in c++ for the queue | Python modules that helps to create a queue | Difference between loop and function | Full form of FAAS | FAAS service on AWS (134:51)
66. Enqueue & dequeue method | Circular queue | Time and space complexity of dequeue & peek operation | Operations of queue | Ways of binary tree traversal | Level order traversal in tree (111:20)
67_90. Searching Algorithm | Level Order Traversal | Module to use Pre-created Queue & How to Create the Same using the Module | Enqueue & Dequeue in the Queue Module (140:12)
75_111. Conditions for all unbalanced cases | Disbalanced node| LL case | Middle node is having a right child | Set the height of a node, (77:08)
76_117. Store the data in physical drive | Sector and block | Indexing concept | m-way search tree (142:23)
77_118. M-way tree | Multi-indexing | Store two data in one node | Time complexity of M way search tree (140:13)
78_122. Rules of B-Tree | Use case of B-Tree | Bottom-top rule | Information that node holds | B+ Tree | Difference between B-tree and B+ tree (132:53)
79. left bias and right bias | Node | 2-3-4 tree means | Which scinerios BTree can be implemented (102:00)
80. Uses cases of RBT | Differentiate between AVL and RBT | List the RBT properties | Draw back of BST | Space and time complexity of RBT (107:59)
81. About Node | Insertdelete operation costly in AVL tree | Facilities of RB tree | Need of rotation algorithm | Coloring technique help in deciding is there need of coloring or not | Red conflict and how to resolve | Use rotation and Coloring | Root and new node (106:37)
82. Use of stats and status inside a pid folder | Implementation priority queue | Binary heap | Min heap and Max heap | Explain complete binary tree (128:08)
83. Priority Queue | Used in OS | problem is solved by Binary Heap | Two ways to implement tree | complexity of Sawpping and Inserting the values in B-Tree | Implementing B-Tree with Array is more beneficial | Heapify (102:17)
84. Use of variable sizeOfHeap and heapSize | Indexaddress of parent from the child node | Code to insert data in a binary heap (86:26)
83._12-04-2022 (103:50)
84._13-04-2022 (94:25)
85._20-04-2022 (104:12)
86._21-04-2022 (124:46)
87_26-04-2022 (140:56)
88_27-04-2022 (111:26)
89_04-05-2022 (104:25)
90_05-05-2022 (68:59)
91_11-05-2022 (107:38)
92_13-05-2022 (124:23)
93_19-05-2022 (124:52)
94_20-05-2022 (88:20)
95. DSA - 24-05-2022 (82:56)
96. DSA - 26-05-2022 (93:57)
97. DSA - 01-06-2022 (108:24)
98. DSA - 08-06-2022 (119:52)
99. DSA - 09-06-2022 (104:41)
100. DSA - 10-06-2022 (81:40)
101. DSA - 14-05-2022 (132:30)
102. DSA - 16-06-2022 (101:02)
103.DSA - 17-06-2022 (94:32)
104. DSA - 21 - 09 - 2022 (132:24)
105. DSA - 22-09-2022 (107:18)
106. DSA - 23-09-2022 (100:37)
Extra Sessions
Python Basic Session 1 (67:36)
Python Basic Session & QnA (129:17)
Python Basic Session & QnA (87:23)
Drive Links
Dynamic Programming Drive Link
83. Priority Queue | Used in OS | problem is solved by Binary Heap | Two ways to implement tree | complexity of Sawpping and Inserting the values in B-Tree | Implementing B-Tree with Array is more beneficial | Heapify
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