The course will cover basic stochastic processes, emphasizing examples from a range of fields.  This will include Markov chains, branching processes, and the diffusion approximation.
Mathematical rigour will be avoided.

Target group: Students with good mathematical and computational ability. Appropriate for students interested in data science, population genetics, statistical physics, etc.

Prerequisites: Linear algebra, and some basic knowledge of probability

Evaluation: Homework (no exam)

Teaching format: Lectures (online/hybrid), problems classes

ECTS: 3 Year: 2024

Track segment(s):
Elective

Teacher(s):
Nicholas Barton

Teaching assistant(s):