Subject interest before course: 7/10
Subject interest after course: 1/10

Exams were not good. Only the first 3 weeks are useful. Afterwards, drop the class, it is not worth your time or energy.

Subject Interest Before Course: 8/10

Subject Interest After Course: 2/10

I enrolled in this class as a CS undergrad. This class is hard, but very manageable; Fragouli does a great job at breaking down the subject and the course notes are very comprehensive.

You do not need to be very good at linear algebra to succeed in this class (Math 33A is probably enough). You should be comfortable representing systems of equations as matrices and taking transposes of block matrices. Although nothing fancy is required in terms of linear algebra, this class is still math-heavy and mostly theoretical.

The homework can get difficult, but prepares you well for exams. If you invest enough time, you will do well. The TAs and discussion sections are also very helpful. There was a group project this quarter (up to 4 people) about applying linear programming to machine learning; you will have to write code and do a report.

The latter half of the class has an algorithmic focus, especially when it comes to Max Flow and its many variants. CS 180 will help, but not by much.

Professor teaches the concept very well intuitively no doubt about it, tests are difficult, Assigments are difficult but the grades are curved, I personally felt that sometime having test which are relatively easier can make you fall in love with subject, if not subconciously we feel, how much ever you know its hard to score in test because concepts covered in class and discussion class problems can help in solving assigments but exams will be completely out of these two. If you are someone new to LP , then they need to put in lot of effort. Sildes are great source of notes and you do not need any text book apart from that. solving statment problems and how to approach should be thought so that we can go above and beyond, if not we will still be trying how to approach and there is no scope for goingbeyond, it seems like I hate the subject to be honest the subject is simple great if you want to understand how optimization works.

One of my favorite profs in EE. Material is very well explained, homeworks are challenging (but doable), and exams are quite hard but the curve helps significantly.

Prep for exams by focusing on lecture review, and for the final make sure to study lots of different max flow/min cut problem variants.

Fragouli is such a good professor by EE standards it's honestly confusing.