Mastering Algorithms: Analysis And Applications

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