DS 2026

Computational Probability

Course Description

Covers the fundamentals of probability theory & stochastic processes. Become conversant in the tools of probability. Clearly describe & implement concepts related to random variables, properties of probability, distributions, expectations, moments, transformations, model fit, basic inference, sampling distributions, discrete & continuous time Markov chains, & Brownian motion. Illustrate most topics with both analytic & computational solutions.


  • Gianluca Guadagni

     Rating

     Difficulty

     GPA

     Sections

    1

    Last Taught

    Fall 2024

  • Thomas Stewart

     Rating

     Difficulty

     GPA

     Sections

    1

    Last Taught

    Fall 2024