Combines topics in data ethics, critical data studies, public policy, governance, and regulation. Address challenges by topic (Health, Education, Culture & Entertainment, Security & Defense, Cities, Environment, Labor). Research how …
Specialized or advanced topics not in DS current course offerings. Requires (a) approval of the program director and (b) an SDS faculty member who will serve as instructor. Propose a …
Graduate-level independent study conducted under the supervision of a specific instructor(s)
The DH Certificate Practicum provides principles for working with humanities materials as data, while maintaining a commitment to humanistic inquiry. Students will learn to integrate digital humanities methods into coursework …
Learning tools and concepts for computing on big data. Learn how to use Spark for large-scale analytics and machine learning. Spark is an open-source, general-purpose computing framework that is scalable …
Covers advanced theoretical concepts for deep neural networks. Topics include convolutional neural networks and their design principles, encoder-decoder architectures, recurrent neural networks, transformers, bounding box detection, image segmentation, generative adversarial …
Current state and future trends in Machine Learning Systems are covered. Topics include hardware systems, software systems, and Machine Learning optimized for metrics beyond predictive accuracy.
Advanced topics within Machine Learning.
This graduate-level course explores the principles, methodologies, and applications of human-centered design (HCD). Students will learn how to create solutions that meet real human needs. The course combines theoretical foundations …
Introduces ways that data and information have historically been constructed in different realms--from medicine to public health to computing--to shed light on the power relationships embedded in some of our …
Transition into principal investigators and generators of data science-based knowledge. Develop practical skills necessary to conduct high quality data science research, advance development into producers and critical consumers of research, …
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Networks provide a unifying framework to study the structure hidden within complex data. This graduate-level course focuses on the fundamental concepts and statistics as well as recent advancements and applications …
Engages students in identification of a research question, a review of the literature and the application of an existing data science tool or technique (algorithm) to that problem. This is …
PhD level Dissertation Research.