| Kommentar |
Biomolecules, cells, organisms, or societies are very complex and noisy physical systems. They are thus characterized by a high degree of uncertainty. A natural approach to deal with uncertainty is probabilistic modeling. In this lecture series we will therefore learn about theoretical concepts and computational tools for probabilistic modeling with a focus on Bayesian modeling. The lecture is accompanied by exercises in which you can try out such methods. The "exam" is a project in which you apply the concepts and tools to the modeling and analysis of complex systems of your choice. |
| Bemerkung |
Biomolecules, cells, organisms, or societies are very complex and noisy physical systems. They are thus characterized by a high degree of uncertainty. A natural approach to deal with uncertainty is probabilistic modeling. In this lecture series we will therefore learn about theoretical concepts and computational tools for probabilistic modeling with a focus on Bayesian modeling. The lecture is accompanied by exercises in which you can try out such methods. The "exam" is a project in which you apply the concepts and tools to the modeling and analysis of complex systems of your choice. |
