Lessons are available for private study. Classes are open by audition only.

Lessons are available for private study. Classes are open by audition only.

Lessons are available for private study. Classes are open by audition only.

This course is for undergraduate students who learned English as an additional language. Giving effective presentations requires a mastery of a broad range of skills. Students will develop skills as diverse as choosing an appropriate topic, creating effective visuals, and designing a speech opening. The overall goal of this course is to develop an awareness and use of common speech types and organizational strategies and to prepare university-level students to deliver presentations in an academic setting.

Data is a core part of most modern applications. This honors course will focus on student-driven, in-depth study of fundamental topics in data management. Activities will include discovery and exploration of interesting datasets, development of educational demonstrations of data management concepts, discussion of advanced challenges in data management, and societal issues associated with data, such as ethics and fairness in a Big Data era.

This colloquium will complement the material in COMPSCI 589 by covering foundational and recent research papers from the machine learning literature. Students will participate in and lead group discussions of papers, and will also write reading responses.

The purpose of this course is to provide students with supplementary material and insights about the software development enterprise. Students meet once a week for a one-hour discussion of software engineering topics whose exploration is intended to provide depth and perspective on the regular material of COMPSCI 320. Topics may be suggested by current events or by problems that may arise in the course of the 320 semester. Students will be required to write a term paper as part of the requirements for this course.

Provides an opportunity for University Honors students enrolled in COMPSCI 335 to take a deeper look at aspects of computer hardware technology and low-level programming, including audio generation and interfacing to various devices. This may involve additional reading and discussion, extra programming projects, conducting experiments.

Representation theory of the symmetric group can be approached using general theory of group representations or with symmetric functions. This area goes back to foundational work of Frobenius, Schur and Yong and a new approach from Okounkov and Vershik. This course will cover representation theory of the symmetric group using these two approaches. The course will also cover the ring of symmetric functions and its relation to the representation theory of the symmetric group and its applications to enumeration.

This course will cover statistical methods now widely used in data analysis, learning and prediction such as regression and classification techniques, feature selection, decision trees, and unsupervised learning methods such as clustering and principal components analysis. The emphasis will be on applying the statistical methods to data sets and understanding the optimization theory that drives these methods.