This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data.

The Peer Advising Program is designed to foster personal and professional development, leadership, and to provide guidance to students in the Public Health Sciences (PHS) major. This Peer Advising Leadership course offers returning Peer Advisors the opportunity to further develop their leadership, organization, and team building skills by serving as Head Peer Advisors.

This seminar focuses on distributed quantum computing (DQC). Topics include but are not limited to circuit knitting; architectures and platforms suitable for DQC; fault tolerance, magic state distillation, and quantum error correcting codes for DQC; applications that can be supported with DQC; the effects of topology and limited interconnectivity; the role of entanglement in DQC; cloud-based quantum computation with remote clients; resource management and scheduling.

Honors Thesis expectations are high. The intended end-product is a traditional research manuscript with accompanying artifact(s), all theses: - are 6 credits or more of sustained research on a single topic, typically conducted over two semesters. - begin with creative inquiry and systematic research. - include documentation of substantive scholarly endeavor. - culminate in an oral defense or other form of public presentation.