Not too easy. Not too difficult.
Course Overview:
This class is very important if you want to better understand efficient programing.
Course highlights:
I learn that for you to be more efficient in solving problems you have to keep practicing.
Hours per week:
9-11 hours
Advice for students:
The class is not hard but you have to study hard if you want to do well in any classes.
This class was tough.
Course Overview:
Lyons is the best math professor I've ever taken a class with. He focuses on concepts more than computation, which makes the material challenging but practical, considering that the course itself is based on algorithms that are rarely executed by hand these days and easily found in software packages like Microsoft Excel. The subject itself is an essential component of applied mathematics, engineering, and computer science, so you will definitely pick up some good intuition on formulating complex everyday problems into ones in the realm of linear optimization.
Course highlights:
The highlights of the course include the intuition behind the duality of linear programming problems as well as some common applications of the cumulative theory behind linear optimization, such as the Transportation Problem and the Scheduling Problem.
Hours per week:
6-8 hours
Advice for students:
Make sure you're comfortable with the basics of linear algebra, especially linear independence, row operations, dot products, and proofs involving matrices! And go to lecture! I can't stress this enough. The textbook becomes pretty hard to follow, because there are a lot of algorithms done by hand. Lyons stops to clarify a lot of concepts and intuition throughout lecture, not to mention he's low-key hilarious. He also never fails to understand a student's question on the first try. He's as good of a listener as he is a lecturer, which makes his lectures a real joy.