Mar 25, 2025 · Design and Analysis of Algorithms is a fundamental area in computer science that focuses on understanding how to solve problems efficiently using algorithms. It is about designing algorithms that are not only correct but also optimal, taking into account factors like time and space efficiency.

Mar 15, 2025 · Analysis of Algorithms is a fundamental aspect of computer science that involves evaluating performance of algorithms and programs. Efficiency is measured in terms of time and space. Basics on Analysis of Algorithms: Why is Analysis Important? Order of Growth; Asymptotic Analysis ; Worst, Average and Best Cases of Algorithms; Asymptotic Notations:

This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.

Design and Analysis of Algorithms covers the concepts of designing an algorithm as to solve various problems in computer science and information technology, and also analyse the complexity of these algorithms designed.

This module covers how to analyze performance of algorithms, models of computation, basic data structures, algorithm design techniques, and common sorting algorithms. [Workload: 1 Week]

In this course you will learn several fundamental principles of algorithm design. You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication.

Learn algorithm design & algorithms for fundamental graph problems including depth-first search, case analysis, connected components, & shortest paths.

An algorithm is a set of rules for carrying out calculation either by hand or on a machine. An algorithm is a sequence of computational steps that transform the input into the output. An algorithm is a sequence of operations performed on data …

This tutorial introduces the fundamental concepts of Designing Strategies, Complexity analysis of Algorithms, followed by problems on Graph Theory and Sorting methods. This tutorial also includes the basic concepts on Complexity theory.

These are my lecture notes from 6.046, Design and Analysis of Algorithms, at the Massachusetts Institute of Technology, taught this semester (Spring 2017) by Professors Debayan Gupta 1 , Aleksander Madry 2 , and Bruce Tidor 3 .