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, problems classes
ECTS: 3 Year: 2021
Track segment(s):
DSSC-PROB Data Science and Scientific Computing - Probabilistic Models
Teacher(s):
Nicholas Barton
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Nick BARTON
- Teaching Assistant: Laura Hayward