COMPSCI189

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COMPSCI 189 - Introduction to Machine Learning

Electrical Engineering and Computer Sciences Undergraduate COE - College of Engineering

Subject

COMPSCI

Course Number

189

Course Level

Undergraduate

Course Title

Introduction to Machine Learning

Course Description

Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication (linear models, trees, neural networks, ensemble methods, instance-based methods); generative and discriminative probabilistic models; Bayesian parametric learning; density estimation and clustering; Bayesian networks; time series models; dimensionality reduction; programming projects covering a variety of real-world applications.

Minimum Units

4

Maximum Units

4

Repeat Rules

Course is not repeatable for credit.

Grading Basis

Default Letter Grade; P/NP Option

Instructors

Abbeel, Bartlett, Darrell, El Ghaoui, Jordan, Klein, Malik, Russell

Prerequisites

MATH 53 and MATH 54; and COMPSCI 70 or consent of instructor.

Credit Restriction Courses

-

Credit Restrictions

Students will receive no credit for Comp Sci 189 after taking Comp Sci 289A.

Term

Fall and Spring

Lecture Hours

3

Discussion Hours

1

Term

Summer

Lecture Hours

6

Discussion Hours

2