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NP-Complete Problems

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University of California, San Diego

via

edX
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Course Features

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Duration

3 weeks

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

10 hours per week

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Teaching Type

Self Paced

Course Description

Step into the area of more complex problems and learn advanced algorithms to help solve them.

This course, part of the Algorithms and Data Structures MicroMasters program, discusses inherently hard problems that you will come across in the real-world that do not have a known provably efficient algorithm, known as NP-Complete problems.

You will practice solving large instances of some of these problems despite their hardness using very efficient specialized software and algorithmic techniques including:

  • SAT-solvers
  • Approximate algorithms
  • Special cases of NP-hard problems
  • Heuristic algorithms

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Basic knowledge of at least one programming language and material of the Algorithmic Toolbox, Data Structures and Algorithms on Graphs classes.

What You Will Learn

NP-completeness and how to deal with it

How to approximate algorithms

How to use heuristic algorithms to solve a problem more quickly when classic methods are too slow

Course Instructors

DK

Daniel Kane

Assistant Professor, Computer Science and Engineering & Dept. of Mathematics

Daniel is an assistant professor at UCSD with a joint appointment between the Department of Computer Science and Engineering and the Department of Mathematics. He holds B.S. from MIT and Ph.D. from Harvard.
AS

Alexander S. Kulikov

Visiting Professor

Alexander is a research fellow at Steklov Mathematical Institute at St. Petersburg, Russia and a visiting professor at University of California, San Diego. He have been teaching algorithms classes for more than eight years.
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