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
DSSC-PROB Data Science and Scientific Computing - Probabilistic Models
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