We learn how to build, use, and critique mathematical models. In modeling we translate scientific questions into mathematical language, and thereby we aim to explain the scientific phenomena under investigation. Models can be simple or very complex, easy to understand or extremely difficult to analyze. We introduce some classic models from different branches of science that serve as prototypes for all models. Student groups will be formed to investigate a modeling problem themselves and each group will report its findings to the class in a final presentation.

This course is the upper-division requirement for BMB majors and focuses on further development of communication skills you will need regardless of your career path after graduation. To be an effective scientific communicator, you need to continue to hone your skills in three dimensions: message (content), presenter (speaker/writer), and audience (reader/listener). Thus, each section of this course will provide support for your continued improvement as a writer/speaker (presenter) and as a reader/listener (audience) using a specific topic (content) in biochemistry and molecular biology.

This course is the upper-division requirement for BMB majors and focuses on further development of communication skills you will need regardless of your career path after graduation. To be an effective scientific communicator, you need to continue to hone your skills in three dimensions: message (content), presenter (speaker/writer), and audience (reader/listener). Thus, each section of this course will provide support for your continued improvement as a writer/speaker (presenter) and as a reader/listener (audience) using a specific topic (content) in biochemistry and molecular biology.

This course is the upper-division requirement for BMB majors and focuses on further development of communication skills you will need regardless of your career path after graduation. To be an effective scientific communicator, you need to continue to hone your skills in three dimensions: message (content), presenter (speaker/writer), and audience (reader/listener). Thus, each section of this course will provide support for your continued improvement as a writer/speaker (presenter) and as a reader/listener (audience) using a specific topic (content) in biochemistry and molecular biology.

Continuation of MATH 127. Elementary techniques of integration, introduction to differential equations, applications to several mathematical models in the life and social sciences, partial derivatives, and some additional topics. The honors section of this course will cover the standard subject matter, as given in the course syllabus, but in greater depth. This means that there will be some emphasis on the underlying theory, that more applications will be included, and that some attention will be paid to history. Active student participation will be encouraged.

A brief introduction to the Python programming language for students with a working knowledge of basic programming concepts. This course is geared towards introductory data science and analytics tasks, and is intended for Informatics majors.

This course covers classical methods in applied mathematics and math modeling, including dimensional analysis, asymptotics, regular and singular perturbation theory for ordinary differential equations, random walks and the diffusion limit, and classical solution techniques for PDE. The techniques will be applied to models arising throughout the natural sciences.

This course will cover several workhorse models for analysis of time series data. The course will begin with a thorough and careful review of linear and general linear regression models, with a focus on model selection and uncertainty quantification. Basic time series concepts will then be introduced. Having built a strong foundation to work from, we will delve into several foundational time series models: autoregressive and vector autoregressive models.

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