Structured population models have become a central tool to explore evolutionary and ecological processes, such as selection gradients or responses to climate change, based on field demographic data. With recent advances in theoretical ecology and computing power, these models have further evolved. Over the last decade, Integral Projection Models (IPMs) have gained popularity because of their simplicity, robustness and flexibility (e.g., no arbitrary discretization of state variables, few parameters, high resolution, incorporate demographic and environmental variability). Although the same set of biologically meaningful outcomes can be obtained from IPMs as those obtained from matrix models, IPMs come with a different set of quantitative and computational challenges. Given the broad applicability of IPMs, the time has come to discuss model selection and formally test which approaches are best for different questions and organisms/growth forms. Participants will learn how to (i) organize and analyze their own data based on examples provided by the organizers, (ii) construct basic and complex IPMs (e.g. using Bayesian approaches to incorporate uncertainty), and (iii) perform basic (population growth rate, stable stage distribution, lifespan, passage time…) and more advanced model construction and demographic projections and perturbations (discrete × continuous state models [e.g. seedbank, dormancy, multiple continuous size classes], age × size models, stochastic models with environmental covariates, latent variables). Modeling will be performed in R using a new package (IPMpack). Following a general introduction, participants will break into groups where, assisted by the group leaders, they will learn about various aspects of IPMs according to expertise and interests. Lunch will not be served, bring your own lunch!