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 rigor 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, problems classes

**ECTS:** 3 **Year:** 2019

**Track segment(s): ****DSSC-PROB** Data Science and Scientific Computing - Probabilistic Models

**Teacher(s): **

Nicholas Barton

**Teaching assistant(s): **

Himani Sachdeva

If you want to enroll to this course, please click: REGISTER

- Teacher: Nick BARTON
- Teaching Assistant: Himani Sachdeva