Approximation Algorithms

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example, because the problems are NP-hard. The goal of the Approximation Algorithms course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations. Prerequisites: In order to successfully take this course, you should already have a basic knowledge of algorithms and mathematics. Here's a short list of what you are supposed to know: - O-notation, Ω-notation, Θ-notation; how to analyze algorithms - Basic calculus: manipulating summations, solving recurrences, working with logarithms, etc. - Basic probability theory: events, probability distributions, random variables, expected values etc. - Basic data structures: linked lists, stacks, queues, heaps - (Balanced) binary search trees - Basic sorting algorithms, for example MergeSort, InsertionSort, QuickSort - Graph terminology, representations of graphs (adjacency lists and adjacency matrix), basic graph algorithms (BFS, DFS, topological sort, shortest paths) The material for this course is based on the course notes that can be found under the resources tab.

状态：Algorithms

状态：Operations Research

中级课程小时

精选评论

4.0评论日期：Feb 24, 2021

Very good course! A nice introduction to approximation algorithms.

4.0评论日期：Oct 10, 2020

Please try to include some more numeric example like load balancing problem in the vertex cover and rest topics

所有审阅

显示：9/9

Suryendu Dalal

3.0

评论日期：Jul 18, 2020

The course was no doubt excellent. At the end of the day you are going to earn a mouth watering certificate signed by one of the best computer scientists in the world. Prof. Mark de Berg. Professor speaks english very well and hence no one will face any problem related to language. Also professor taught the course extremely well. But unfortunately this course is completely inactive. All the questions in discussion forums remains unanswered. There was a problem is Week 2 Assignment 'PTAS for Load Balancing', where your correct answer will be considered wrong. Mentors of this course are sitting idle. They do not provide any assistance to the students. This course really needs a mentor who is active.

Dongyun Kim

5.0

评论日期：May 3, 2021

Short but compact course that discusses important topics. The quizes and programming homeworks are challenging enough to help to check your studying procedure. Prof. Mark de Berg is an amazing instructor and gives clear lecture videos. One small tip will be to check the Errata sheet before studying. Overall a compact and helpful course.

ChocolateCharlie

5.0

评论日期：Nov 23, 2020

Nice introductory course which combines both theory and practice. Though these algorithms are covered in the course, a previous experience with greedy algorithms and dynamic programming might be helpful.

Jakob B.

5.0

评论日期：Jan 27, 2021

Excellent short course on approximation algorithms. Good course material, presentations and exercises.

Kalina Bakardzhieva

5.0

评论日期：Sep 23, 2023

The material is explained very clearly. The examples are very useful. Thank you for this content!

周柏宇

5.0

评论日期：Aug 13, 2020

A great introductory course to the approximation algorithms.