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Intro to Theoretical Computer Science

Free Course

Dealing with Challenging Problems

Related Nanodegree Program

Introduction to Programming

About this course

This class teaches you about basic concepts in theoretical computer science -- such as NP-completeness -- and what they imply for solving tough algorithmic problems.

What you will learn

  1. Challenging Problems
    • An introduction to tough problems and their analysis.
  2. Understanding Hardness
    • What we mean when a problem is "hard" and the concept of NP-completeness.
  3. Showing Hardness
    • Tools to let you recognize and prove that a problem is hard.
  4. Intelligent Force
    • Smart techniques to solve problems that should – theoretically – be impossible to solve.
  5. Sloppy Solutions
    • Gaining speed by accepting approximate solutions.
  6. Poking Around
    • Why randomness can be of help – sometimes. An introduction to complexity classes.
  7. Ultimate Limits
    • Problems that no computer can ever solve. In theory.

Prerequisites and requirements

You should have a basic understanding of algorithms (such as CS215) and programming (such as CS101). No prior knowledge about theoretical computer science required!

See the Technology Requirements for using Udacity.

Why take this course?

At the end of this course, you will have a solid understanding of theoretical computer science. This will not only allow you to recognize some of the most challenging algorithmic problems out there, but also give you powerful tools to deal with them in practice.

Learn with the best.

  • Sebastian Wernicke
    Sebastian Wernicke


  • Sean Bennett
    Sean Bennett


  • Sarah Norell
    Sarah Norell