Since I've already taken Math 170 sequence courses, I walked into this class without expecting to learn much. However, this was not the case. I thought I've already learned probability extremely well, but Professor Dolecek's teaching truly made my understanding clearer than ever. One of the highlights of this course was definitely the coding final project since we were able to simulate probabilistic scenarios with computation, and I had tons of fun with it. The professor was also pretty accommodating by creating an additional midterm to alleviate the pressure of depending on a single midterm. Overall, I would highly recommend taking this course with Professor Dolecek.

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.

In my opinion, Professor Dolecek is severely underrated on bruinwalk, and I definitely enjoyed her class the most this quarter.
Dolecek's lectures reminded me of those MIT open-class videos that I have seen on Youtube. She was very organized and explained the concepts pretty well. She always answered questions that people had and encouraged class participation. This is why even though her lectures were recorded, most people still preferred to show up in person. I think the biggest downside about her lectures was that she handwrote all her notes on the whiteboard and it could be hard to read sometimes. Regardless, you could always ask her to clarity what each symbol meant.
The exams were okay. I went over her past exams in the test bank, and I realized that her exams used to be a lot harder. Maybe that is why she has such bad reviews on bruinwalk. Anyway, our midterm and final were pretty well designed and similar to the HW, with maybe one or two questions that were kind of challenging/tricky. If you understand the HW, you should get at least a 90 on the exams. Be sure to check your answers though, we did not get to use a calculator during the exams and they did not grade our exams very nicely (you would lose a lot of points for making an algebraic error).
Some of the HW questions involved coding in matlab and there was a matlab project. I did not find coding in matlab particularly difficult with the help of the internet.

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.

Prof Dolecek is one of the best lecturers in the ECE department. This is one of the few upper div classes where I feel that I can fully absorb the content taught in the 2-hour lecture, and be immediately able to do most homework problems (without having to do too much of my own mental gymnastics). Her approach of writing on the whiteboard, having us take our own notes, and asking us lots of questions really helped me stay engaged, but this might not work as well for those who learn better with slides or by watching recordings. She does, however, upload PDF notes from a previous quarter.

Very chill class. Only one exam and it was not math heavy. Good introduction to data science and machine learning.

a very straightforward class -- watch the lectures and follow instructions and you will get an A

Free

If you're a CS major (or basically any major not required to take 131A) don't take it imo. I would have taken Math170E or Stats100A in hindsight. The topics are interesting and presented well, but the TAs this year sucked at making exams. We had a pretty wide distribution for the midterm (70 median with 1 std dev getting you to a 90). Homeworks were pretty easy outside of some really dumb questions. Towards the end it became all calculus and no probability. Also, the final exam was terrible this winter. The TAs who wrote the exam changed one of the PDFs for a question worth 1/6 of the final exam about halfway through. There were too many questions also. A couple parts of some questions were just wacky algebra that we've never seen on discussion, homework, or in-class. It was a top 2 worst final exam experience and it's not #2.