This course looks into the past, present, and future of technologies that impact labor, with an eye to empowering students with knowledge about the social, economic, and political dimensions of the tools they use both inside and outside of work. The course covers labor history, whistleblowers, and hidden histories of common technologies that reorient common assumptions about what technologies can do, and what they have done in the past.

Provides a foundation in discrete mathematics, data structures, algorithmic design and implementation, computational complexity, parallel computing, and data integrity and consistency. Case studies and exercises will be drawn from real-world examples (e.g., bioinformatics, public health, marketing, and security).

Provides an in-depth exploration of probabilistic and statistical methods used to understand, quantify, and manage uncertainty. Learn foundational concepts in probability and statistics, simulation techniques, and modern approaches to parameter estimation, decision theory, and hypothesis testing. Topics include parametric and nonparametric methods, Bayesian and frequentist paradigms, and applications of uncertainty in real-world problems. 

This course will equip students with some of the most commonly used deep learning architectures. We will explore feed-forward networks, convolutional neural networks, UNETs, encoders-decoders, generative adversarial networks and transformers. We will also analyze tools of explainable AI. Focused on environmental applications, students will apply these techniques to real-world data, solving problems in prediction, pattern recognition, and data-driven insights. Solid background in probability, statistics, and in coding (preferably Python) is recommended for enrollment in this course.

Focuses on principles & theories of law related to healthcare delivery, management & administration. Examines the application of laws on healthcare liability prevention & the risks managers face. Explores legal & ethical issues in healthcare systems; and investigates the healthcare administrator as decision-maker, leader and moral agent. Evaluates situations with potential ethical/legal implications.

An intensive overview of cloud infrastructure and their role in data science. Topics will include storage as a service, ephemeral computing resources, auto-scaling, and event-driven workloads. Special attention will be paid to cloud-native design patterns, which are built assuming the unique functionality of cloud computing resources.

A course for advanced short story writers. Student manuscripts are discussed in individual conference and in class. May be repeated with different instructor. For instructions on how to apply to this class, see www.engl.virginia.edu/courses. Prerequisite: Instructor permission.

This seminar uses Hepatitis C to explore the promises and pitfalls of the U.S. healthcare system. Once the deadliest infectious disease in America, Hepatitis C now has a highly effective cure¿yet millions remain untreated. Why? Through science, policy, and ethics, we¿ll examine barriers such as drug pricing, insurance, stigma, and social determinants of health, and develop creative, interdisciplinary solutions. No science background required.

Provides foundational overview of the structure/function of US healthcare system including challenges and opportunities to develop competence in healthcare management, promotes critical discussion of history and current status of healthcare delivery systems. Examines challenges facing providers, patients and policy makers, and uses current events to explore healthcare controversies. Prerequisite: Bachelor's Degree

For more than 200 years, Americans and Europeans have exchanged ideas about prison reform. Today, few Europeans look to America for examples of prison reform. Why would they? This course explores the US prison system as well as why and when Norway adopted a different approach to crime and punishment than the U.S.