2021-2022 Academic Catalog

Nov 21, 2024

2021-2022 Academic Catalog [ARCHIVED CATALOG]

DSCI 216 - Stochastic Computing

This course is about dealing with uncertainty that appears in virtually all areas of data science and computer science. This will be accomplished with tools and techniques for its measurement, description, evaluation, and ultimately making decisions under uncertainty.

The course will approach these goals using a three-fold approach, namely problem, theory, and prototype (PTP). We will motivate major topics by discussing a problem. The purpose of discussion of the problem is to give context behind why a particular supporting topic in probability was developed or what it is intended to address. The problem will be followed by theory. This concerns rigorous mathematical definition and tools for their manipulation in order to address the problem. Emphasis will be placed on approaches that are amenable to implementation. Finally, theory will be followed by prototype. The purpose of the prototype aspect of the course is to train students in the development of models that serve a useful purpose.

Prerequisites: MATH 121 - Calculus II or MATH 125 - Honors Calculus II and

CSCI 121 - Data Structures or CSCI 124 - Honors Introduction to Computing

Anticipated Terms Offered: Fall 2021