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.

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Course Cost
Free
Timeline
Approx. 2 months
Skill Level
Intermediate
Included in Course
  • Rich Learning Content

  • Interactive Quizzes

  • Taught by Industry Pros

  • Self-Paced Learning

  • Student Support Community

Join the Path to Greatness

This free course is your first step towards a new career with the Machine Learning Engineer Nanodegree Program.

Free Course

Intro to Theoretical Computer Science

Enhance your skill set and boost your hirability through innovative, independent learning.

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Course Leads

  • Sebastian Wernicke
    Sebastian Wernicke

    Instructor

  • Sean Bennett
    Sean Bennett

    Instructor

  • Sarah Norell
    Sarah Norell

    Instructor

What You Will Learn

Lesson 1: Challenging Problems

An introduction to tough problems and their analysis

Lesson 2: Understanding Hardness

What we mean when a problem is “hard” and the concept of NP-completeness

Lesson 3: Showing Hardness

Tools to let you recognize and prove that a problem is hard

Lesson 4: Intelligent Force

Smart techniques to solve problems that should – theoretically – be impossible to solve

Lesson 5: Sloppy Solutions

Gaining speed by accepting approximate solutions

Lesson 6: Poking Around

Why randomness can be of help – sometimes. An introduction to complexity classes.

Lesson 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.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals
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