Summer 2025 Computer Science W4771 section V01

MACHINE LEARNING

Call Number 11528
Points 3
Grading Mode Standard
Approvals Required None
Instructor Nakul Verma
Type LECTURE
Method of Instruction On-Line Only
Course Description

Basic statistical principles and algorithmic paradigms of supervised machine learning.

Prerequisites: 
Multivariable calculus (e.g. MATH1201 or MATH1205 or APMA2000), linear algebra (e.g. COMS3251 or MATH2010 or MATH2015), probability (e.g. STAT1201 or STAT4001 or IEOR3658 or MATH2015), discrete math (COMS3203), and general mathematical maturity. Programming and algorithm analysis (e.g. COMS 3134). 
COMS 3770 optionally satisfies all math prerequisites for this course.

Web Site Vergil
Subterm 07/07-08/15 (B)
Department Video Network
Enrollment 6 students (99 max) as of 12:06PM Friday, October 31, 2025
Subject Computer Science
Number W4771
Section V01
Division Interfaculty
Fee $395 CVN Course Fee
Note VIDEO NETWORK STUDENTS ONLY
Section key 20252COMS4771WV01