Understand machine learning fundamentals, cybersecurity, and deep learning principles. Explore how machine learning algorithms can be leveraged to address prevalent cybersecurity issues, such as malware detection, spam filtering, anomaly detection, …
This course introduces first-year graduate students in the humanities and social sciences to the knowledge and skills fundamental to success in graduate school. Particular topics vary.
This course is designed for first year Graduate students in the Computer Engineering Program to help orient new graduate students to the current research topics, available research tools, software and …
Covers the fundamental concepts of uncertainty in artificial intelligence (AI). Students will explore various techniques and models used to handle uncertainty in AI and machine learning systems, including Bayesian deep …
Project oriented course that will research specific climate problems, proposing new solution to decision makers at local & state level. Course expands understanding of broad societal scope relevant to climate …
Introduces physics-aware deep learning (PADL), an emerging approach that embeds physical laws into neural networks for accurate, efficient modeling. Topics include differential equations, physics-informed neural networks, neural operators, and PyTorch …
Provides an exploration of foundational concepts in modern time series modeling and analysis. The course covers both classical statistical and signal processing methods and contemporary deep learning models.
This course considers some of the leading accounts of the origins, growth, and persistence of nationalism. Among other topics to be considered are ethnicity and nationalism; religion and nationalism; gender …
Introduces classic and contemporary theory and research on the social psychology of stigma, primarily from the perspective of the stigmatized. Topics include stigma's origin and nature, stigma and self-concept, stereotype …
Students register for this course to complement an industry work experience. Topics focus on the application of engineering principles, analysis, methods and best practices in an industrial setting. A final …