Current instructor
Original student reviews · all captured dates
Easiest A of my life, but I still learned a lot. To be honest, it was not necessary to go to lecture at all; reading her notes was enough to learn the material. Made a feared class incredibly easy and was also always nice and smiling. Examples and activities were done very slowly, for better or for worse.Rate My Professors ↗
I really like her. tbh I cannot speak for her other classes, but for Math 319, she explains everything very clearly. Her notes are well organized, she is very kind, and the exams are clear and fair. I genuinely enjoyed the class and would highly recommend taking it with her.Rate My Professors ↗
Her lectures are very clear and go over many practice examples. If you pay attention in class and do the posted practice exam/review before exams, the exams will go very well for you. She is very nice and wants people to succeed in her class. She posted weekly surveys to see what was going well or needed improvement, and she cares about feedback.Rate My Professors ↗
Unclear lectures and likes to start completely new topics at the last 5 minutes of every lecture. Would not recommend, but she is very nice and caring.Rate My Professors ↗
Would not recommend. Lectures were not very valuable, slow & improper explanations. Notes are easy to go through after lectures though.Rate My Professors ↗
Professor Le is a truly caring professor. She wants her students to succeed, and if you go to her outside of class, she will help you with any questions. The lectures were sometimes rushed or confusing, but throughout the year the pacing mostly got better. Lecture attendance isn't mandatory, but it's hard to catch up unless you can teach yourself.Rate My Professors ↗
Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.
MATH 535 teaches mathematical methods for data science, including matrix factorizations, optimization, and probabilistic models.
Offering recorded · Fall 2026
historical GPA · grades
Spring 2022–Spring 2026| Term | Course | Title |
|---|---|---|
| Fall 2026 | MATH 535 | Mathematical Methods in Data Science |
Teaching history may be incomplete. Course pages contain course-specific feedback and citations.
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