The Design and Analysis of Algorithm Masterclass 2023
What you’ll learn
Enhance Your Logical Thinking Abilities
Learn various Popular Data Structures and their Algorithms.
Knowing Algorithm Well helps you to Solve the Problem in a Better Way.
Learn Big O, Big Omega Big Theta Notation
Linear Search, Recurrence Relations
Factorial, Tail Recursion
Towers of Hanoi
Merge Sort, Quick Sort, Heap Sort
Knapsack Problem, Minimum Spanning Tree: Kruskal’s Algorithm, Minimum Spanning Tree: Prim’s Algorithm
Huffman’s Codes – Building Huffman Tree, Dijkstra’s Algorithm,Bellman Ford Algorithm, Floyd Warshall Algorithm
Brute Force Matcher
Pattern Pre-Processing
The Knuth Morris Pratt Algorithm
n-Queens Algorithm
Graph Coloring, Hamiltonian Cycles
0/1 Knapsack Problem
15 Puzzle Problem
NP Completeness and Approximation Algorithms
Will get to know Real time uses of all Algorithm
Get the answer of your “WHY” part behind use of every Algorithm
Requirements
Idea of Programming (Good To Have – NOT Mandatory)
Some Basic Mathematics (Good To Have – NOT Mandatory)
Basic Concepts of Data Structures (Good To Have – NOT Mandatory)
Little Familiarity with Graph Theory (Good To Have – NOT Mandatory)
Description
The algorithm is used everywhere. People Don’t know how Complex algorithms they are executing when doing there day to day tasks like Riding a Bi-Cycle, Travelling from one place to another even Watering Gardens. If you are Coder then the Knowledge of algorithms is Very much important for you. The knowledge of Algorithm teach you How to Think to solve a Problem?The algorithm is the concept that differentiates one average software engineer and one better software engineer. In our daily life in the industry, we used different kinds of algorithms to make the system faster, better, and more efficient.But the problem is 90% of the freshers and graduates don’t have the basic knowledge of algorithms. That is the reason we make this Design and Analysis of algorithm Masterclass.What you are Going to Learn?Asymptotic Notations, Recursion, Divide and Conquer, Dynamic Programming, Dijkstra’s, Bellman-Ford, Floyd Warshall Algorithm, Kruskal’s Algorithm, Knapsack Problem, String Matching with Finite Automaton, Heap sort, Huffman Codes, n-Queens Algorithm, Rat in Maze, 0/1 Knapsack Problem, 15 Puzzle Problem, NP-Completeness, Approximation Algorithms12 hours of HD content [Updated on 2022 December]Assignment [Updated]Study Note [Updated]Certificate Every Single Day we will check your questions and solve your queries.Topics covered :Enhance Your Logical Thinking AbilitiesLearn various Popular Data Structures and their Algorithms.Knowing Algorithm Well helps you to Solve the Problem in a Better Way.Learn Big O, Big Omega Big Theta NotationLinear Search, Recurrence RelationsFactorial, Tail RecursionTowers of HanoiMerge Sort, Quick Sort, Heap SortKnapsack Problem, Minimum Spanning Tree: Kruskal’s Algorithm, Minimum Spanning Tree: Prim’s AlgorithmHuffman’s Codes – Building Huffman Tree, Dijkstra’s Algorithm, Bellman-Ford Algorithm, Floyd Warshall AlgorithmBrute Force MatcherPattern Pre-ProcessingThe Knuth Morris Pratt Algorithmn-Queens AlgorithmGraph Coloring, Hamiltonian Cycles0/1 Knapsack Problem15 Puzzle ProblemNP-Completeness and Approximation AlgorithmsWill get to know Real-time uses of all AlgorithmGet the answer of your “WHY” part behind the use of every Algorithm
Overview
Section 1: Introduction & Overview
Lecture 1 About The Instructor
Lecture 2 Objective of the Course
Lecture 3 Prerequisite to take the Course
Lecture 4 Course Curriculum Overview
Section 2: Introduction to Algorithms
Lecture 5 1.Introduction to Algorithms
Section 3: Asymptotic Notations
Lecture 6 2.Big O, Big Omega and Big Theta
Lecture 7 Problems on Big O
Lecture 8 Algorithmic Complexity with Asymptotic Notations
Section 4: Recursion
Lecture 9 Linear Search, Greatest Common Divisor
Lecture 10 Factorial, Tail Recursion
Lecture 11 Recurrence Relations, Substitution Method
Lecture 12 Towers of Hanoi
Section 5: Divide and Conquer
Lecture 13 Binary Search
Lecture 14 Master Method
Lecture 15 Tiling a Defective Chessboard
Lecture 16 Merge Sort Part #1
Lecture 17 Merge Sort Part #2
Lecture 18 Quick Sort
Section 6: Dynamic Programming
Lecture 19 Fibonacci Numbers
Lecture 20 Rod Cutting
Lecture 21 Matrix Chain Multiplication
Lecture 22 Longest Common Sub Sequence
Section 7: Greedy Algorithms
Lecture 23 Knapsack Problem
Lecture 24 Minimum Spanning Tree: Kruskal’s Algorithm
Lecture 25 Disjoint Sets and Kruskal’s Algorithm
Lecture 26 Job Sequencing with Deadlines
Lecture 27 Heap
Lecture 28 Heap Sort
Lecture 29 Priority Queue
Lecture 30 Minimum Spanning Tree: Prim’s Algorithm
Lecture 31 Huffman’s Codes – Building Huffman Tree
Lecture 32 Huffman’s Codes – Printing Huffman Codes
Section 8: Shortest Path Algorithms
Lecture 33 Dijkstra’s Algorithm Part #1
Lecture 34 Dijkstra’s Algorithm Part #2
Lecture 35 Dijkstra’s Algorithm Part #3
Lecture 36 Bellman Ford Algorithm
Lecture 37 Topological Sort
Lecture 38 Shortest Path by Topological Sort
Lecture 39 Floyd Warshall Algorithm
Section 9: The Problem of String Matching
Lecture 40 Brute Force Matcher
Lecture 41 String Matching with Finite Automaton
Lecture 42 Pattern Pre-Processing
Lecture 43 The Knuth Morris Pratt Algorithm
Section 10: Backtracking
Lecture 44 Rat in Maze
Lecture 45 n-Queens Algorithm Part #1
Lecture 46 n-Queens Algorithm Part #2
Lecture 47 Graph Coloring Part #1
Lecture 48 Graph Coloring Part #2
Lecture 49 Hamiltonian Cycles I
Lecture 50 Hamiltonian Cycles II
Lecture 51 Subset Sum
Section 11: Branch & Bound
Lecture 52 Introduction to Branch and Bound
Lecture 53 0/1 Knapsack Problem
Lecture 54 The 15 Puzzle Problem
Lecture 55 Solvability of 15 Puzzles
Section 12: NP Completeness
Lecture 56 Introduction to NP Completeness
Lecture 57 Reductions
Lecture 58 The Circuit Satisfiability Problem
Lecture 59 More NP Complete Problems 1
Lecture 60 More NP Complete Problems 2
Section 13: Approximation Algorithms
Lecture 61 Approximation Algorithms
Lecture 62 The Vertex Cover Problem
Computer science students,Software working professionals who wants to learn better way to Solve a Problem
Course Information:
Udemy | English | 12h 33m | 12.61 GB
Created by: Up Degree
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