Short Course Description
The course will introduce graduate students to models in population biology. We will build models, analyze them using mathematical and computational methods, and fit them to empirical data using statistical methods such as maximum likelihood and Bayesian inference. Examples will include models from ecology, evolution, epidemiology, and social behavior. In each case, we will introduce a research question, design a model, choose a method, apply it using the Python program language, analyze and visualize the results, and discuss the conclusions.
This is a graduate-level (MSc, PhD) course that includes several home assignments and a final project. It requires basic background in mathematics, statistics, ecology, and evolution.
The course will be taught in English.
Full syllabus will be available to registered students only
