Spring 2026 Computer Science W4771 section 002

MACHINE LEARNING

Call Number 12366
Day & Time
Location		 MW 4:10pm-5:25pm
451 Computer Science Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Tony B Dear
Type LECTURE
Method of Instruction In-Person
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
Department Computer Science
Enrollment 0 students (110 max) as of 10:05AM Friday, October 10, 2025
Subject Computer Science
Number W4771
Section 002
Division Interfaculty
Section key 20261COMS4771W002