This course is intended for participants in the Undergraduate Student Opportunities in Academic Research (USOAR) program.

This course is intended for participants in the Undergraduate Student Opportunities in Academic Research (USOAR) program.

The course explores government contracting, how the government procures products and services, and opportunities created through government regulation. Pre-requisite: STS 1500 or ENGR 1020 or ENGR 2595-Engineering Foundations II.

This advanced-level Turkish course explores the rich culinary heritage of Turkey, focusing on its diverse regions, historical influences, and the role of food in cultural identity. Students will gain an understanding of how Turkey's cuisine reflects its multicultural past and present, blending flavors from the Ottoman Empire, Central Asia, the Middle East, and the Mediterranean.

Provides overview of cyber security (CS) policies, laws, regulations, and ethical considerations that can be used to help protect and improve an organization's security posture. Explores related topics including ethics, CS policy requirements and controls, compliance, and implementation issues. Examines modern CS regulations and frameworks, and the various policies and procedures that may be used in an organization's security strategy.

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.

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.