Analysis of Algorithm
Created by Arnab Chakraborty, Last Updated 07-Aug-2019, Language:English
Analysis of Algorithm
Simply Easy Learning
Created by Arnab Chakraborty, Last Updated 07-Aug-2019, Language:English
Description
Analysis of Algorithm is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem. These estimates provide an insight into reasonable directions of search for efficient algorithms. This video tutorial will give you a great understanding on Analysis of Algorithm 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 Analysis of Algorithm and its applications. Enthusiastic readers who would like to know more about algorithms and those who wish to implement algorithms 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
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Analysis of Algorithm
1 Lectures 00:01:03-
Analysis of Algorithms - Getting Started
Preview00:01:03
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Algorithm Introduction
1 Lectures 00:03:22-
Analysis of Algorithm - Definition
Preview00:03:22
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Complexity of Algorithm
7 Lectures 00:26:52-
Space and Time Complexity of an Algorithm
Preview00:06:39 -
Time Complexity Big-Oh Notation
Preview00:04:04 -
Time Complexity Big-Omega Notation
00:03:59 -
Time Complexity Big-Theta Notation
00:04:42 -
Asymptotic Notations GATE Exercise 1
00:01:54 -
Asymptotic Notations GATE Exercise 2
00:02:34 -
Time Complexity GATE Exercise
00:03:00
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Algorithm and Classification
9 Lectures 00:33:11-
Algorithm Classification - Introduction
00:03:08 -
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
Preview00:03:14 -
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
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Elementary Data Structure
20 Lectures 01:28:26-
Definition of Data Structure
00:03:09 -
Classification of Data Structure
00:02:48 -
Lower Triangular Sparse Matrix
00:06:16 -
Tridiagonal Sparse Matrix
00:07:28 -
Sparse Matrix Another Example
00:04:31 -
Array GATE Exercise
00:02:30 -
Stack GATE Exercise
00:03:48 -
Binary Tree GATE Exercise
00:03:15 -
Binary Tree Traversals GATE Exercise 1
00:04:11 -
Binary Tree Traversals GATE Exercise 2
00:03:42 -
Binary Search Tree Introduction
00:06:18 -
Ranked Binary Search Tree
Preview00:06:29 -
Binary Search Tree GATE Exercise 1
00:03:44 -
Binary Search Tree GATE Exercise 2
00:02:12 -
AVL Search Tree GATE Exercise
00:07:16 -
B-Tree - Definition and Properties
00:06:29 -
B-Tree - An Example
00:08:38 -
Sorting GATE Exercise 1
00:01:47 -
Sorting GATE Exercise 2
00:01:21 -
Hashing GATE Exercise
00:02:34
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Sets and Set Operations
4 Lectures 00:31:10-
Sets and Disjoint Set Union
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Simple Set Union and Simple Set Find Algorithms
00:10:37 -
Weighted Union Algorithm
00:08:52 -
Collapsing Find Algorithm
00:06:56
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Recursion
10 Lectures 00:52:41-
Definition of Recursion
00:09:01 -
Recursion Variations Direct
Preview00:05:02 -
Recursion Variations Indirect
00:01:54 -
Recursion Variations Nested
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Recursion Variations Excessive
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Recursion Variations Tail
00:04:21 -
Recursion Overheads
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Towers of Hanoi as an Example of Recursion
00:11:02 -
Recursion GATE Exercise 1
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Recursion GATE Exercise 2
00:04:10
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Divide and Conquer
4 Lectures 00:28:17-
Divide and Conquer Algorithm
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Quick Sort
00:08:38 -
Merge Sort
00:07:21 -
Execution Tracing of Merge Sort
00:07:37
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The Greedy Method
5 Lectures 00:30:20-
Properties of Greedy Algorithm
00:06:25 -
A Sample Greedy Algorithm
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Greedy Method Job Sequencing With Deadline
00:07:49 -
Greedy Algorithm GATE Exercise
00:04:29 -
Greedy Method Job Sequencing With Deadline Example
00:05:54
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Dynamic Programming
7 Lectures 00:54:47-
Dynamic Programming Matrix Chain Multiplication
00:09:49 -
Dynamic Programming Matrix Chain Multiplication - Example
00:06:20 -
Matrix Multiplication GATE Exercise
00:03:20 -
Dynamic Programming Travelling Salesman Problem
00:07:38 -
Dynamic Programming Travelling Salesman Problem - Example
00:09:13 -
Knapsack Problem
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Knapsack Algorithm and Example
00:11:14
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Back Tracking Algorithm
7 Lectures 00:54:45-
Back Tracking Algorithm N-Queen’s Problem
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Back Tracking Algorithm 8-Queen’s Problem
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Back Tracking Algorithm N-Queen’s Algorithm
00:07:42 -
Back Tracking Hamiltonian Cycles
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Back Tracking Algorithm For Hamiltonian Cycles
00:11:10 -
Back Tracking Graph Coloring Problem
00:11:02 -
Back Tracking Graph Coloring Algorithm
00:09:24
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Branch and Bound
2 Lectures 00:15:32-
Branch and Bound 15-Puzzle Problem
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Branch and Bound 15-Puzzle Problem Game Tree
00:09:49
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NP-Hard and NP - Complete Problems
3 Lectures 00:18:15-
NP-Hard and NP - Complete Problems
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Non-Deterministic Algorithms
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Some Important Issues on P And NP Algorithms
00:04:15
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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 twenty-six+ 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