| |
Nov 05, 2024
|
|
|
|
|
2023-2024 Undergraduate Catalog [ARCHIVED CATALOG]
|
BUAD 442 - Interpretable Data Models Credit(s): 3
INTERPRETABLE DATA MODELS
Component: Lecture
This course focuses on interpretable data modeling for insight and interpretability. Students will learn to model and represent business problems using the language of probabilistic graphical models, translate those models into a form amenable to computation, and visually present computational insights back to stakeholders in a way that communicates insight and inspires action. Major topics include: Probabilistic Models, Causal Modelling, Probabilistic Programming (e.g. Turing.jl or Stan), Sampling Algorithms (e.g. MCMC), and Probabilistic Inference.
Repeatable for Credit: N Allowed Units: 3 Multiple Term Enrollment: N Grading Basis: Student Option
PREREQ: BUAD 345 .
General Education Objectives:
|
|
