CS 3190 - Found. of Data Analysis

Institution:

University of Utah

Subject:

Computer Science

Description:

This class will be an introduction to computational data analysis, focusing on the mathematical foundations. The goal will be to carefully develop and explore several core topics that form the backbone of modern data analysis topics, including Machine Learning, Data Mining, Artificial Intelligence, and Visualization. This will include some background in probability and linear algebra, and then various topics including Bayes' rule and connection to inference, gradient descent, linear regression and its polynomial and high dimensional extensions, principal component analysis and dimensionality reduction, as well as classification and clustering. We will also focus on modern models like PAC (probably approximately correct) and cross-validation for algorithm evaluation. Prerequisites: 'C-' or better in (CS 2100 AND CS 2420 AND MATH 2270) AND Full Major status in Computer Science OR Data Science OR Software Development Corequisites: 'C-' or better in (MATH 3070 OR CS 3130 OR ECE 3530)

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

08/15/2022 - 08/14/2024 08/15/2019 - 08/14/2022 

Institution Website:

www.utah.edu

Phone Number:

(801) 581-7200

Regional Accreditation:

Northwest Commission on Colleges and Universities

Calendar System:

Semester

General Education

• No items found

The Course Profile information is provided and updated by third parties including the respective institutions. While the institutions are able to update their information at any time, the information is not independently validated, and no party associated with this website can accept responsibility for its accuracy.