
Intro to Theoretical Computer Science
Summary
This class teaches you about basic concepts in theoretical computer science -- such as NP-completeness -- and what they imply for solving tough algorithmic problems.
Expected Learning
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.
Syllabus
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.
Required Knowledge
You should have a basic understanding of algorithms (such as CS215) and programming (such as CS101). No prior knowledge about theoretical computer science required!
Free
Intermediate
8 weeks
Sebastian Wernicke
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