Graduate Programs

This course is designed to develop your understanding of the fundamental concepts in data mining and how they can be used to answer questions about real-world problems. These methods, and the underlying models, can be used to learn from existing data to make predictions about new data. The course will help you understand the mindset of creating a data project pipeline by covering topics on model development, causal inference, and traditional data mining. The class will both emphasize individual work and also team work by helping students solidify their knowledge through a final project.

Location

( 7:00PM - 7:00PM)

This course presents the fundamental concepts of database design and use. It provides a study of data models, data description languages, and query facilities including relational algebra and SQL, data normalization, transactions and their properties, physical data organization and indexing, security issues and object databases. It also looks at the new trends in databases. The knowledge of the above topics will be applied in the design and implementation of a database application using a target database management system as part of a semester-long group project.

Location

( 7:00PM - 7:00PM)

This course will cover foundational concepts in descriptive analyses, probability, and statistical inference.  Topics to be covered include data exploration through descriptive statistics (with a heavy emphasis on using R for such analyses), elementary probability, diagnostic testing, combinatorics, random variables,  elementary distribution theory, statistical inference, and statistical modeling. The inference portion of the course will focus on building and applying hypothesis tests and confidence intervals for population means, proportions, variances, and correlations. Non-parametric alternatives will also be introduced. The modeling portion of the course will include ANOVA, and simple and multiple regression and their respective computational methods. Students will be introduced to the R statistical computing environment. 

Location

(MWF 9:00AM - 11:50AM)

This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.

Location

( 7:00PM - 7:00PM)

This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness.

Location

( 7:00PM - 7:00PM)

This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees.

Location

( 7:00PM - 7:00PM)

This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations.

Location

( 7:00PM - 7:00PM)

This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations.

Location

( 7:00PM - 7:00PM)

This course provides master's students who are currently completing their final required coursework, or with special circumstances like an approved reduced courseload, with the opportunity to work full-time on their degrees. Students will make significant progress toward completing their degrees.

Location

( 7:00PM - 7:00PM)

This course affords graduate students visiting the University of Rochester full-time student status. Visiting students will engage in research, discussion, and/or professional training in partnership with an academic department or faculty member.

Location

( 7:00PM - 7:00PM)

This course is designed for PhD students who have completed all required coursework but still need to finalize specific degree requirements under less than half-time enrollment.

Location

( 7:00PM - 7:00PM)

This course provides PhD students who have completed or are currently completing 90 credits of coursework and have fulfilled all degree requirements (except for the dissertation) with the opportunity to work full-time on their dissertation. Students will make significant progress toward completing their degrees. Available during summer semester only.

Location

( 7:00PM - 7:00PM)

This course provides PhD students who have completed or are currently completing 90 credits of coursework and have fulfilled all degree requirements (except for the dissertation) with the opportunity to work full-time on their dissertation. Students will make significant progress toward completing their degrees.

Location

( 7:00PM - 7:00PM)