Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing or maximizing convex functions over convex sets. Many classes of convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard.
This series by Dr. Ahmad Bazzi focuses on applications instead of theory behind convex optimization. In other words, you get to learn where and how to apply convex optimization to real world problems, such as Finance, Transportation, Machine learning, Wireless communications, Game Theory and much more. Just click the play button and the red subscribe button to show support to the free courses.