Complexity Theory Basics

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This video 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. Thats why big O, big theta and big omega have 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 wel as NP. These concepts are fundamental if we want to have a good grasp ondata structures and graph algorithms, so these topics are definitely worth considering. Hope you will like it!
  • Introduction
    • Introduction
  • Algorithms Analysis
    • Complexity theory basics
    • Complexity theory illustration
    • Complexity notations - big ordo
    • Complexity notations - big omega
    • Complexity notations - big theta
    • Complexity notations - example
    • Algorithm running times
    • Complexity classes
    • Analysis of algorithm - loops
    • Case study O(N) - linear search
    • Case stude O(logN) - binary search
    • Case study O(N*N) - bubble sort
    • Measuring running times
  • Course Data
    • Course data
    • Discounted coupons for other courses
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