Overall this is a math class, with minimal programming questions sprinkled in. Midterms, final, lectures, and 75% of the hw questions were all math proofs/questions. However, the exams were pretty easy and straightforward. They were open book, which was a lifesaver since the questions were heavily based on her lectures. Recommend taking 10/10

Overall, I'm very happy with this class and its instructors (Lara Dolecek, Lev Tauz, Mitra Debarnab). I come from a CS background and have taken 1-2 machine learning classes (a few years ago) where they never really delved into the mathematical details of distributions, their origins and properties. This class helped fill that gap for me and I feel more confident in my understanding of the maths behind ML.

As for the class itself, it covers pretty much everything from the initial axioms that define probability up to common statistical measures such as covariance, squared error and correlation. I took this class remotely via the MSOL program and had a grade breakdown as follows:
-25% Homework (8 in total)
-25% Midterm (open book)
-25% Assignment (solo)
-25% Final (open book)

10 weeks is not a lot of time for this and it shows: the class moves at a fast pace, particularly towards the end. Even in the week of the final, a sizable number of new topics were introduced (fortunately, they did not feature in the exam). I personally did not do as well in the final exam, but got good grades otherwise, ending up with 88% overall.

Some tips for new students:
-The following concepts are useful to know: set theory, multivariable calculus (partial derivatives, double integrals, limits, convergence), convolution, Fourier transform, sums and sequences, complex numbers, gamma function and delta function. You don't need to know all of them, but most should be familiar.
-The textbook is your friend: it covers the content of the lectures at a higher level of detail and has useful examples when you're struggling with the homework.
-The discussions are helpful, as they will go over more advanced problems that the lectures do not address. Also, they are usually a bit more difficult than the exam, so if you take the time to solve and understand those you should be fine.
-The assignment is an easy way to boost your grades as the concepts are not particularly difficult. However, it does take quite a while to write up the MATLAB programs and report, so make sure to start it before the last week so you have some idea of how long it will take you.

I did not really like her.
She basically wrote the course reader on the board.
She has an accent and is hard for to understand.
She is not very clear and does not do very many examples.
Questions on the hw are impossible and u need to have past solutions.

Midterms and finals were fair but her curve was non existent/bad.
Did above average on final, average on midterm, 100's on all the hw's, top 10% on the matlab project and i got a B.

The TA was pretty whatever, tl dr i would not recommend taking the class with her.

This class is fine. The exams weren't too hard, the homework load was fine. Homework was so light at the beginning and then became very time consuming at the end. The class for me was easy in the beginning(with combinatorics and stuff) but at the end it got much more complicated. The lectures are good and the professor aims to connect the material to real life applications with example problems which is good. Handwriting on the notes is sometimes hard to read, but just ask the professor if you don't know what she wrote and she'll tell you. The project is fine, but try to start on it early and ask lots of questions about instructions if you are unsure.

Solid professor. Lectures worth attending and work load isn't too high. Final exam average was really low but curved.

Lots of material is covered in this class. Lara knows her stuff but can be very intimidating sometimes. Final was ridiculously difficult.

131 is a hard class in general (unless you're a math major taking this for fun, in which case it was probably child's play), but Lara is a good professor.

Lots of content. Workload is not too bad, a couple problems a week and a MATLAB project towards the end. Lectures were definitely worth the two hours. Midterm and final have grade distributions are low but curved. Would take this class again with this professor.

The exam is very tricky. It seems the professor want to lower the grade as much as possible. Grading is harsh. You will lose a lot of points on the stuff that you know how to do. Probability is not an easy class, but this professor make it harder. Her lecture is okay, but her hand-writing is extremely difficult to decipher.

Damn this class was tough. Attending lectures is a must since the assigned book in my experience was too complicated with its mathematical notation of simple concepts. The midterm and final exams were also quite tough with the midterm average at around 67. However, I do give Professor Dolecek props because her lectures were clear and well paced for the amount of material she taught.
Also there is a final project on matlab that spills over into finals week so figure out how to schedule your time with working on it.