Aimed at: Masters students
Background: Linear algebra.
Some experience with statistics and probability is preferable, but not necessary. Some experience with rings and ideals is preferable, but not necessary.
Course text: Lectures on Algebraic Statistics by Mathias Drton, Bernd Sturmfels and Seth Sullivant.
Recommended additional reading:
1. S. Lauritzen: Graphical Models, Oxford University Press, New York, 1996
2. D. A. Cox, J. Little, and D. O'Shea: Ideals, Varieties, and Algorithms: An introduction to computational algebraic geometry and commutative algebra, Springer, 2007
3. Sturmfels: Solving Systems of Polynomial Equations, American Mathematical Society, 2002
4. Piotr Zwiernik: Semialgebraic Statistics and Latent Tree Models, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, 2015