Data Structure Online Training
Created by Arnab Chakraborty, Last Updated 05Sep2019, Language:English
Data Structure Online Training
Simply Ease Learning
Created by Arnab Chakraborty, Last Updated 05Sep2019, Language:English
Description
Data Structures are the programmatic way of storing data so that data can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way. This video tutorial will give you a great understanding on Data Structures needed to understand the complexity of enterprise level applications and need of algorithms, and data structures.
Audience
This video tutorial is designed for students interested in learning data structure and its applications. Enthusiastic readers who would like to know more about data structures and those who wish to implement data structures themselves may start from here. These video classes have been developed based on the latest GATE syllabus and will be useful for undergraduate students of Computer Science and Information Technology as well as those preparing for GATE exams. It will also be helpful for students in preparing them for their Engineering Syllabus.
Course Content

Data Structure
1 Lectures 00:01:05
Data Structure  Getting Started
Preview00:01:05


Data Structure Introduction
2 Lectures 00:05:57
Definition of Data Structure
Preview00:03:09 
Classification of Data Structure
Preview00:02:48


Algorithm and Complexity Analysis
8 Lectures 00:30:14
What is an Algorithm?
00:03:22 
Space and Time Complexity of an Algorithm
00:06:39 
Time Complexity BigOh Notation
00:04:04 
Time Complexity BigOmega Notation
00:03:59 
Time Complexity BigTheta Notation
00:04:42 
Asymptotic Notations GATE Problem 1
00:01:54 
Asymptotic Notations GATE Problem 2
00:02:34 
Time Complexity GATE Problem
00:03:00


Algorithm and Classification
9 Lectures 00:33:11
Algorithm Classification Introduction
Preview00:03:08 
Algorithm Classification Simple Recursive Algorithm
00:03:12 
Algorithm Classification Back Tracking Algorithm
00:04:17 
Algorithm Classification Divide and Conquer
00:02:17 
Algorithm Classification Dynamic Programming
00:03:14 
Algorithm Classification Greedy Algorithm
00:06:25 
Algorithm Classification Branch and Bound
00:05:09 
Algorithm Classification Brute Force
00:03:41 
Algorithm Classification Randomized Algorithm
00:01:48


Operation on Signals
8 Lectures 00:45:41
String Introduction
00:02:05 
String Operations
00:06:07 
String Processing Insert
00:04:41 
String Processing Delete
00:04:06 
String Processing Replace
00:05:10 
Pattern Matching Algorithm  Brute Force
00:09:52 
Knuth Morris Patterson (KMP) Pattern Matching Algorithm
00:05:03 
KMP Pattern Matching Algorithm Example
00:08:37


Arrays
12 Lectures 01:14:59
Definition of Linear Array
00:04:44 
Insert Operation on an Array
00:08:58 
Delete Operation on an Array
00:07:06 
Memory Representation of One Dimensional Array
00:05:35 
Memory Representation of Two Dimensional Array in Row Major
00:07:19 
Memory Representation of Two Dimensional Array in Column Major
00:05:45 
Saddle Point of a Matrix
00:09:00 
Saddle Point Implementation Algorithm
00:05:47 
Lower Triangular Sparse Matrix
00:06:16 
Tridiagonal Sparse Matrix
00:07:28 
Another Sparse Matrix Example
00:04:31 
Array GATE Problem
00:02:30


Recursion
10 Lectures 00:52:41
Definition of Recursion
00:09:01 
Recursion Variations Direct
00:05:02 
Recursion Variations Indirect
00:01:54 
Recursion Variations Nested
00:05:29 
Recursion Variations Excessive
00:05:37 
Recursion Variations Tail
00:04:21 
Recursion Overheads
00:03:04 
Towers of Hanoi as an Example of Recursion
00:11:02 
Recursion GATE Problem 1
00:03:01 
Recursion GATE Problem 2
00:04:10


Linked Lists
18 Lectures 01:29:26
Linked List Introduction
00:10:40 
Linked List Traversing and Processing
00:03:55 
Linked List Finding Maximum and Minimum Node Info
00:05:16 
Linked List Searching on Unsorted Linked List
00:03:25 
Linked List Searching on Sorted Linked List
00:04:14 
Linked List Insert a New Node as The First Node
00:03:09 
Linked List Insert a New Node After Search Node
00:05:34 
Linked List Deletion of a Node With Given Info
00:06:52 
Header Linked List Introduction
00:04:47 
Header Linked List Insertion as The First Node
00:03:46 
Circular Header Linked List Introduction
00:03:36 
Two Way Linked List Introduction
00:02:42 
Two Way Linked List Insertion
00:05:50 
Two Way Linked List Deletion
00:04:57 
Reverse of a Linked List
00:07:29 
Polynomial Representation Using a Linked List
00:02:00 
Polynomial Addition Using Linked List Example
00:04:32 
Polynomial Addition Using Linked List Algorithm
00:06:42


Stacks
10 Lectures 00:55:36
Stack  Introduction
00:01:06 
Stack Operations Introduction
00:06:55 
Stack Operations  PUSH & POP
00:05:53 
Implementing Two Stacks in One Array
00:06:54 
Implementing Four Stacks in One Array
00:06:03 
Stack Application Evaluation of Post Fix Expression
00:05:17 
Stack Application Evaluation of Post Fix Expression Example
00:04:51 
Stack Application Infix to Postfix Conversion
00:06:32 
Stack Application Infix to Postfix Conversion Example
00:08:17 
Exercise on Stack
00:03:48


Queues
4 Lectures 00:24:31
Queue Operations Introduction
00:07:45 
Queue Operations Insert
00:06:29 
Queue Operations Delete
00:05:08 
Priority Queue
00:05:09


Trees
22 Lectures 01:55:47
Binary Tree and Terminologies
00:07:41 
Binary Tree Representation in Memory
00:10:51 
Binary Tree Traversals
00:09:40 
Binary Tree Traversals Exercise 1
00:04:11 
Binary Tree Traversals Exercise 2
00:03:42 
Algorithm of InOrder Traversal
00:02:16 
Algorithm of PreOrder Traversal
00:01:52 
Algorithm of PostOrder Traversal
00:01:48 
Binary Search Tree Introduction
00:06:18 
Searching an Item in BST
00:07:47 
Insertion of an Item in BST
Preview00:05:47 
Deletion of a Node From BST With One Or Zero Child Node
00:05:22 
Deletion of a Node From BST With Two Children
00:10:26 
Deleting a Node From BST
00:03:38 
Ranked Binary Search Tree
00:06:29 
Extended Binary Tree Or 2Tree
00:04:26 
Huffman’s Algorithm With Example
00:05:15 
Huffman’s Coding
00:06:01 
Huffman Code Example
00:03:06 
Binary Tree Example
00:03:15 
Binary Search Tree Example 1
00:03:44 
Binary Search Tree Example 2
00:02:12


Balanced Trees
6 Lectures 00:52:19
AVL Tree  A Height Balanced Tree
00:13:11 
AVL Search Tree LL and RR Rotation
00:07:51 
AVL Search Tree RL and LR Rotation
00:08:54 
AVL Search Tree Example
00:07:16 
BTree Definition and Properties
00:06:29 
BTree an Example
00:08:38


Heap Tree & Sort
7 Lectures 00:41:00
Heap Tree
00:05:21 
Heap Tree Insertion Operation
00:05:03 
Heap Tree Insertion Operation Example
00:06:12 
Heap Tree Deletion Operation
00:05:04 
Heap Tree  Deletion Operation Example
00:09:41 
Heap Sort
00:06:31 
Heap Sort GATE Problem
00:03:08


Sorting Techniques
13 Lectures 01:29:47
Bubble Sort
00:10:41 
Modified Bubble Sort
00:04:08 
Insertion Sort
00:10:33 
Selection Sort
00:08:53 
Quick Sort
00:08:38 
Merge Sort
00:07:21 
Execution Tracing of Merge Sort
00:07:37 
Radix Sort Example
00:05:08 
Radix Sort Algorithm
00:11:03 
Exercise 1 On Sorting
00:01:47 
Exercise 2 on Sorting
00:01:21 
External Sorting  Introduction
00:04:46 
External Sorting Sample Implementation
00:07:51


Searching Techniques
5 Lectures 00:35:11
Linear Search
00:07:23 
Linear Search on Sorted Array
00:04:32 
Binary Search
00:08:59 
Trie Structure Algorithm
00:04:38 
Trie Structure Example
00:09:39


Hashing
6 Lectures 00:39:25
Hashing Introduction
00:07:02 
Hashing Collision and Collision Resolution
00:08:18 
Hashing Chaining
00:06:35 
Hashing Chaining Example
00:05:59 
Hashing With Example
00:08:57 
Exercise on Hashing
00:02:34

Arnab Chakraborty
Corporate Trainer
Prof. Arnab Chakraborty is a Calcutta University alumnus with B.Sc. in Physics Hons Gold medalist, B. Tech and M. Tech in Computer Science and Engineering has twentysix+ years of academic teaching experience in different universities, colleges and thirteen+ years of corporate training experiences for 170+ companies and trained 50,000+ professionals. He has also completed MBA from Vidyasagar University with dual specialization in Human Resource Management and Marketing Management. He is NLP and PMP trained, "Global DMAIC Six Sigma Master Black Belt" certified by IQF (USA). He is certified by ISA (USA) on "Control and Automation System". He is "Global ITIL V3 Foundation" certified as awarded by APMG (UK). Qualified for "Accredited Management Teacher" by AIMA (India). "Star Python" Global Certified from Star Certification (USA). "Certified Scrum Master (CSM)" Global Certification from Scrum Alliance (USA). He is also empaneled trainer for multiple corporates, e.g. HP, Accenture, IBM etc