
This course offers an introduction to optimization models and their applications, ranging from machine learning and statistics to decisionmaking and control, with emphasis on numerically tractable problems, such as linear or constrained leastsquares optimization. The course covers two main topics: practical linear algebra and convex optimization.
The image on the left is taken from an antenna array design example. It shows how we can design an array of antennas that concentrate their emitting energy in one target direction, while mininizing the power due to thermal noise.

To communicate: use Piazza.
Link to UC Berkeley Schedule of classes: here.
