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STA 9891: Machine Learning/Data Mining at Baruch College

3 credits · Fall 2026

Machine Learning/Data Mining (STA 9891) at Baruch College has 1 way to take it in Fall 2026. 1 of 1 section has an open seat right now.

The professor is: Kamiar Rahnama Rad.

Compare them below, check the days and times, and add the course to your schedule.

Requirements

Prerequisite: STA 9705

About this course

This course concentrates on classification-oriented tools for data mining. Topics will include support vector machines, neural networks, regression trees, bagging, boosting and additive trees, nearest-neighbors methods, and cluster analysis. Students will implement these techniques on big-data case studies throughout the semester. Examples will include instances of both supervised and unsupervised learning.

Professors for STA 9891 at Baruch, Fall 2026

Ordered chillest first. A Chill Rank compares a professor with other CUNY professors on Rate My Professors difficulty, rating and would-take-again; it needs at least 3 ratings. How it works

STA 9891 sections, times and seats

Seat status as of Oct 4, 6:51 PM ET. Seats can change between refreshes. How fresh is this?

Chill Rank compares professors using Rate My Professors reviews, from Chill to Brutal. What each rank means

UMA-LEC Regular
Mon · 6:05 PM - 9:00 PM
B - Vert 12-116
Kamiar Rahnama RadChill Rank 4 of 5: Busy?★ 2.5(71)Difficulty 3.4/5 · 31% would take again
In PersonOpen

Questions about STA 9891 at Baruch

Who teaches STA 9891 at Baruch in Fall 2026?
Kamiar Rahnama Rad is listed for Fall 2026. Each name links to a page with their Chill Rank and Rate My Professors numbers.
Is STA 9891 at Baruch hard?
It depends on the professor. Across the 1 professor with a Chill Rank, students on Rate My Professors give an average difficulty of 3.4 out of 5. The Chill Rank above compares them directly.
What if a STA 9891 section is full?
Try another section, join the waitlist in CUNYfirst if there is one, or ask the department. You can also watch a full section and get an email when a seat opens; you still enroll yourself in CUNYfirst.