Honestly... she's probably the best you're going to get for 113. Her curve is set so that median is a high B+, pushing to an A-.

But the way she runs her classes is problematic. Her examples and lecture notes are too simple, and are designed to teach you definitions and to present formulas to solve questions with (e.g. determining if a system is linear, TI, casual, stable). The homeworks and discussion sections are designed with similar principles, but much harder.

Then you realize the goddamn midterms are EVEN HARDER, but on top of that, a large portion will usually involve proving some crazyass property and the questions related to homework and discussions make up maybe only 30% of the exam. And to nobody's surprise, the class got absolutely dumpstered.

So on the final, the focus was on stuff similar to homework questions, which is good! But the test is now 36. FUCKING. PAGES. Just endless questions (i.e. endless torture). So that's already bad design. But on top of that, because of her grading scheme, and the fact that the midterm averages were so low and unrelated to the design of her final exam, it made me realize that I totally didn't need to even take any of the midterms. That's not a good outlook on the class, just fyi.

Anyway she has an extra credit project. Do it lol.

This class, and the prof frankly, were a mess from start to finish. The book that the entire class is based on is from the 70's and is horrible at explaining the concepts taught in class, and the professor does the same along with it. Expectations for the class are extremely vague, with lessons barely correlating with any of the exams or homework. Additionally, there are two group projects that you are required to work on, and the first project was horribly explained and it took over a week to get clarification answers, with the project taking an excessive amount of man-hours with no clarity on how grading worked. Finally, as stated earlier, the homework and exams had almost nothing to do with what was taught in class, often asking very obscure questions that would often take much longer to decipher than to answer.
Summary: The book, lectures, assignments, and the class as a whole are extremely unorganized and I would recommend avoiding this class unless you have a good understanding of graph theroy previously

People have polarized opinions about this class, possibly due to the fact that the contents were quite "quirky." The homework problems were mostly proof-based, but the exam problems geared more towards application, so most students were surprised and had a hard time decipher what those problems meant. Overall, I feel like the lectures were well-explained, and the professor was super nice during office hours. What I liked the most about this class were the open ended projects that allowed us to apply the theoretical concepts on real-world problems. Even though the first project was a mess due to some floppy wordings, the overall experience was enjoyable. My only complaint was about the TA, who seldom answered questions, and was super lazy. I would recommend taking this class with this professor, but just be aware of who your TA is.

I loved this class! She's a great lecturer who explains clearly and is very willing to answer questions/repeat concepts. Her tests were interesting and very fair. Though the final exam was significantly harder than the midterm, I suspect the curving was generous for the final grades. The homework was also interesting and short with the exception of the first couple Matlab assignments, but even these were reasonable. Not to mention she has a very nice, almost motherly personality! I honestly would take her just for her personality, but the wonderfully balanced homework and tests are the icing on the cake!

Take her! If not for this class, then for something else, because I bet she'll be great for other courses, too. (And from what I heard, she has been!)

Professor Fragouli is one of the best professors in the ECE department, and I would highly recommend taking this class with her. Her lectures are crystal clear, and she posts her lectures and lecture notes online for review. Professor Fragouli is very approachable and always willing to help during office hours. While her tests are challenging, they're fair and graded with integrity. The tests won't be exactly like homework or discussions, as they are a bit harder, if you understand the concepts you'll do well. She also does a really good job of making systems and signals very interesting to learn about, as with some other professors, apparently this class can be pretty dry.

Genuinely one of my favorite professors at UCLA.

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.

I thought this class was pretty cool. You learn about the most common concepts and theorems in graph theory and how to formulate problems in science and engineering as graph theory problems. Fragouli herself is a good lecturer and a very pleasant person, and was very helpful at answering questions in class and in office hours. The TA was also pretty helpful and active at answering questions on Campuswire. There were 6 homework assignments, and instead of a midterm and a final there were 3 quizzes, of which the lowest score was dropped. There was also a coding project in Python which was pretty interesting but really frustrating to work on; the project specifications were confusing, and generating and plotting the results was very computationally expensive. As someone with a decent amount of experience working in Python and with NumPy, I spent hours optimizing my code to get it to run faster, and it still took more than an hour to plot all the results. A lot of my classmates said their code took even longer, so just a fair warning that you can't start the project last minute. There was also extra credit for contributing on Campuswire and for having the best performing project. Anyway, I'm pretty sure the project was graded on completion (?), and I didn't do very well on the quizzes, but the curve was generous so I still got an A. Overall, I enjoyed this class and I would recommend this class as an ECE elective (I petitioned it to count toward my math tech breadth actually).

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.

This was a challenging class without having taken some of the lower divs that offer a primer on some of the topics. The class moved fairly quickly. Homeworks generally take a long time if you are doing them by yourself. I thought it was necessary to go to lecture because the notes helped a lot on the problem sets. Her lectures follow a logical progression through the topics. Overall a positive experience I definitely learned something in the process.