Mastering Algorithms: Analysis And Applications
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English
| Duration: 2h 20m
Algorithm, Complexity, Analysis, Design techniques
What you'll learn
Design Efficient Algorithms in solving Complex real time Problems
Explore various algorithm design techniques to solve problems in polynomial time
Employ various approaches to solve Greedy and Dynamic Algorithms
Utilize Backtracking , Branch and Bound Paradigms
Requirements
Completion of Data Structures and Algorithms
Description
"Mastering Algorithms: Analysis and Applications" is a comprehensive course designed to equip learners with a deep understanding of algorithms and their practical applications. From fundamental concepts to advanced techniques, this course covers everything you need to know to become proficient in algorithm analysis and implementation.Through a combination of lectures, practical examples, and hands-on exercises, you will learn how to analyze the efficiency of algorithms, understand their behavior, and apply them to solve real-world problems. Delving into the core principles of algorithms, this course offers a comprehensive exploration of various algorithmic techniques and their rigorous analysis.Topics covered include:Introduction to algorithm analysis and complexity theorySorting and searching algorithmsData structures such as arrays, linked lists, trees, and graphsDynamic programming and greedy algorithmsGraph algorithms including shortest path, minimum spanning tree, and network flowPractical applications of algorithms in areasWhether you're a beginner looking to build a solid foundation in algorithms or an experienced programmer aiming to enhance your problem-solving skills, this course offers valuable insights and practical knowledge to help you master algorithms and excel in your field. Join us on this journey to unlock the power of algorithms and unleash your potential. Join us on this enlightening journey and unlock the power of algorithms to drive innovation and excellence.
Overview
Section 1: Introduction
Lecture 0 Introduction
Lecture 1 Evaluation of Algorithms- Space Complexity
Lecture 2 Evaluation of Algorithms - Time Complexity
Lecture 3 Recursion Tree
Section 2: Divide and Conquer
Lecture 4 Divide and Conquer - General Strategy
Lecture 5 Linear Search
Lecture 6 Binary Search
Lecture 7 Quick Sort
Section 3: Greedy Algorithm
Lecture 0 Greedy Algorithm - Introduction
Lecture 8 Huffman Encoding
Section 4: Dynamic Programming
Lecture 9 Matrix Chain Multiplication
Lecture 10 Least Common Subsequence
Section 5: Backtracking
Lecture 0 Backtracking - General Strategy
Lecture 11 N Queen's Problem
Section 6: Branch and Bound
Lecture 0 Branch and Bound - General Strategy
Lecture 0 Travelling Salesperson Problem
Lecture 12 0/1 Knapsack Problem
Novice individuals who have acquired knowledge of data structures and algorithms
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