Complexity Theory Basics
Asymptotic complexity, complexity theory, running times, complexity classes
Description
This course is about algorithms running times and complexity theory. In order to be able to classify algorithms, we have to define limiting behaviors for functions describing the given algorithm. That's why big O, big theta and big omega came to be. We are going to talk about the theory behind complexity theory as well as we are going to see some concrete examples. Then we will consider complexity classes including P as well as NP. These concepts are fundamental if we want to have a good grasp of data structures and graph algorithms, so these topics are definitely worth considering. Hope you will like it!
This course is meant for everyone who are interested in algorithms and wants to get a good grasp of complexity theory.
Asymptotic complexity, complexity theory, running times, complexity classes
Description
This course is about algorithms running times and complexity theory. In order to be able to classify algorithms, we have to define limiting behaviors for functions describing the given algorithm. That's why big O, big theta and big omega came to be. We are going to talk about the theory behind complexity theory as well as we are going to see some concrete examples. Then we will consider complexity classes including P as well as NP. These concepts are fundamental if we want to have a good grasp of data structures and graph algorithms, so these topics are definitely worth considering. Hope you will like it!
This course is meant for everyone who are interested in algorithms and wants to get a good grasp of complexity theory.
You do not have permission to view the full content of this post. Log in or register now.