Introduction to Graduate Algorithms

Provided by:
0/10 stars
based on  0 reviews
Provided by:
Cost FREE
Start Date On demand

Course Details

Cost

FREE

Upcoming Schedule

  • On demand

Course Provider

Udacity online courses
Udacity gives students the opportunity to create hands-on projects that can be put into their portfolios and used to demonstrate their skills to future employers. You'll have a personal coach who helps provide feedback on your assignments and projects to assist you in reaching your goals and staying on track in your online classes. Throughout your education experience, you'll be able to track your development, complete in-class projects, have access to interactive exercises and videos and ...
Udacity gives students the opportunity to create hands-on projects that can be put into their portfolios and used to demonstrate their skills to future employers. You'll have a personal coach who helps provide feedback on your assignments and projects to assist you in reaching your goals and staying on track in your online classes. Throughout your education experience, you'll be able to track your development, complete in-class projects, have access to interactive exercises and videos and earn a verified certificate at the end of the course as proof of all that you've learned. You'll be learning from knowledgeable professors across various schools and parts of the globe. Learn about computer science from Dave Evans, an instructor at the University of Virginia, or delve into app development with Samantha Ready, a Developer Evangelist at Salesforce.com.

Provider Subject Specialization
Sciences & Technology
102 reviews

Course Description

This is a graduate-level course in the design and analysis of algorithms. We study techniques for the design of algorithms (such as dynamic programming) and algorithms for fundamental problems (such as fast Fourier transform or FFT). In addition, we study computational intractability, specifically, the theory of NP-completeness. The main topics covered in the course include: dynamic programming; divide and conquer, including FFT; randomized algorithms, including RSA cryptosystem and hashing using Bloom filters; graph algorithms; max-flow algorithms; linear programming; and NP-completeness.
Introduction to Graduate Algorithms course image
Reviews 0/10 stars
0 Reviews for Introduction to Graduate Algorithms

Ratings details

  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars

Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

No reviews yet. Be the first!

Rating Details


  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars

Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.