8 courses with the subject DS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
This course introduces students to fundamental data science methods and processes. Students will learn the fundamentals of collecting, storing, managing, cleaning, visualizing, exploring, analyzing, and presenting data. Special attention will be paid to ethical use of data to inform decision-making.
GIS software allows users to incorporate the location of observations into their data analysis. Some GIS capabilities include: Generating heat maps, measuring and analyzing distance, and identifying optimal business location. This is an applied course, and students will learn to find and download spatial data, and to use GIS software to answer questions in economics, business, and digital humanities.
Survey of languages and applications used to create visualizations for large datasets. This course also discusses principles of human perception and human computer interaction that are used to design effective visuals.
Exploration and application of professional ethical standards as well as Catholic and Benedictine values to ethical issues arising from data collection, management, use, and analysis.
This course is a case-based class that simulates the detection and prevention of fraud in various financial institutions. Students will learn to use data analytics to identify fraudulent patterns and create rules to block fraudulent behavior. Using examples from credit card companies, retirement account management companies, and others, students will assess fraud reports and build a filtering system. Special attention is paid to financial trade offs and ethical issues.
This course builds on methods in 388 and introduces new tools such as logistic regression and gradient analysis. Prerequisite: DS388
A project-based course, with student groups analyzing a need at the college or within the local community. This is a writing-intensive course.
Special topics for Data Analytics
Source: Belmont Abbey College's catalog, linked per course · table learning_unit · CourseShelf publish 61
