ISTA410

Download as PDF

ISTA410 - Bayesian Modeling and Inference

School of Information Undergraduate UA - UA General

Course Description

Bayesian modeling and inference is a powerful modern approach to representing the statistics of the world, reasoning about the world in the face of uncertainty, and learning about it from data. It cleanly separates the notions of representation, reasoning, and learning. It provides a principled framework for combining multiple source of information such as prior knowledge about the world with evidence about a particular case in observed data. This course will provide a solid introduction to the methodology and associated techniques, and show how they are applied in diverse domains ranging from computer vision to molecular biology to astronomy.

Min Units

3

Max Units

3

Repeatable for Credit

No

Grading Basis

GRD - Regular Grades A, B, C, D, E

Career

Undergraduate

Enrollment Requirements

017241

May be convened with

INFO510

Name

Lecture

Workload Hours

3

Optional Component

No

Typically Offered Main Campus

Spring