This week we continued to learn about algorithm analysis and really got in to the definitions of Big- O(upper bound), and big-Omega (lower bound).We also learned how to prove if a function of Big O and Big Omega.
The importance of this week was understanding the concept of time complexity and growth rate of functions. With this understanding, proving whether functions are Big-O, Big-Omega, or Big-Theta(growth in-between big-Omega and Big-O).
This understanding is important in understanding how the speed in an algorithm is essential in concise programming.
