Exposes students to foundational knowledge in the area of analytics, especially as it relates to machine learning. The focus is on methods needed to prepare data for machine learning models, how to evaluate the output of ML models and engineering features.

Moves deeper into current best practices around data engineering in industry. Topics will review basic data collection, ingestion, processing, and storage, moving beyond to data governance, security, pipeline orchestration, monitoring and maintenance, optimization, and documentation. Relies heavily on DevOps principles of automation, continuous improvement, and an understanding of the entire software/data lifecycle.

Engage with and train in the use of key concepts in machine learning and math: OLS estimator for regression; logistic regression & maximum likelihood estimator; multiple linear regression; principal components analysis & multiple correspondence analysis; neural networks; logarithms; probability distributions; integrals; multivariate optimization; matrix notation, eigen-math, and matrix decomposition; infinite power series & Taylor series.

Explore mathematical foundations of inferential and prediction frameworks, with emphasis on computation, used to learn from data. Frequentist, Bayesian, and Likelihood viewpoints are all considered. Topics: principles of estimation, optimality, bias, variance, consistency, sampling distributions, estimating equations, information, bootstrap methods, ROC curves, shrinkage, large sample theory, prediction optimality versus estimation optimality.

Explores human aspects of cyber security -- including security training and awareness, cyber ethics, hacktivism, hacker culture -- with emphasis on human motivations and responses. Examines common human-centered attacks, such as phishing, social engineering, and other psychological manipulation.

Develops strong writing competencies for technical fields, including communication of complex information to a variety of audiences through various print and online media. Teaches students to write, organize, edit, and design information with clarity and accuracy. Covers organizing, managing, communicating, and facilitating technical information. Topics include conciseness, simplicity, information arrangement, presentation, and readability.

Provides an overview of the laws governing healthcare institutions and the ethical dilemmas facing healthcare managers and providers; reviews ethical principles utilized to examine health care issues. Evaluates the procedures followed by healthcare organizations in making legal and ethical decisions; addresses such contemporary issues as cloning, euthanasia, and organ donation. Prerequisite: Admission to BPHM or BIS program.

This is one of the two introductory core courses in the GCCS major. It surveys academic research on topics that are salient to contemporary global commerce: the global and the local; illicit trade; the body across borders; global labor; technology and digital infrastructures; trade and physical infrastructures; companies and climate change; global economic governance; and social goals in the international division of labor.

How do developing countries in the global South navigate the emergence of renewed great power competition? This class will explore the impact of European & non-Euro imperialism on large parts of the developing World. We will seek to answer this question by looking at the engagement of countries & actors in the global South with established and emerging powers in an increasingly multi-polar World.

In this experiential, workshop-based course, students will develop leadership skills in translating ideas into action, using UVA's Grounds as a living lab for sustainability - the campus as a sustainability classroom. Students will gain insight into a process in which individuals can catalyze change to solve global problems and advance strategic goals on a local level though a place-based, project-based, and human-centered approach.