BIO 180: Mathematical Modeling for Biology
The analysis of quantitative data is at the heart of modern biology. This course will provide basic statistical analysis and mathematical modeling skills for 21st-century life scientists. The course will focus on the practical application of modern statistical tools for complex, real-world data sets, and the elements of using difference equations to predict the growth of animal and cell populations, the mutualistic or competitive interactions between species, demographic change, and the spread and control of epidemics. The course will use the “R” statistical language, a very powerful and freely available software tool.
MATH 298: Fundamental Concepts in Computational and Applied Mathematics
Starting research in applied mathematics can be like learning a new language. There are many new terms and basic facts that must be mastered in order to even start a conversation about one’s research. In addition, there are many expectations and new skills beyond those taught in standard undergraduate mathematics courses that must be learned to become a successful graduate student in applied mathematics. This course will introduce the student to some of the fundamental concepts used in computational and applied mathematics. We will not attempt to go into any one area in depth; rather we will present a survey of some of the key ideas and tricks used by practicing computational mathematicians. Along the way, our tour will highlight some of the classic numerical analysis papers and the top algorithms used today, including those from linear algebra, nonlinear equations, optimization, discretizations and differential equations, and spectral methods. These ideas will also be highlighted through several case studies taken from real-world applications in computational sciences.