Courses

Course Description: An overview of advanced computational statistics for signal and network analysis with a wide variety of social, genomic and neuroscientific applications. All course modules include a hands-on component. Students have the chance to apply the computational methods and skills learned throughout the course on data analytic assignments and a research project.

Course Objectives: Upon successful completion of this course, the student should be able to

• Demonstrate an advanced understanding of computational statistics for signal and network analysis

• Demonstrate the ability to apply the computational procedures taught throughout the course in data analytic assignments

• Demonstrate the ability to implement variants of the computational procedures taught in the course on a research project

Target audience: Senior undergraduate and graduate students in Biostatistics, Statistics, Computer Science, Electrical Engineering, with an interest and research needs in learning advanced computational techniques in complex signal and network analysis

Prerequisites: Calculus II required, Calculus III desirable; Stat equivalent of STAT512/513 and BIOS701/757/711.