Undergraduate Prerequisites: First-Year Writing Seminar (e.g., WR 120); CAS CS111, CDS DS110, ENG E K125, or equivalent; CAS MA225, CAS CS235, CDS DS122, or equivalent; C AS MA242, CAS CS132, CDS DS121, or equivalent; CAS MA581, CA - Graduate Prerequisites: CAS CS111, CDS DS110, ENG EK125, or equivalent; CAS MA225, CAS CS235, CDS DS122, or equivalent; CAS MA242, CAS CS132, CDS DS121, or equivale nt; CAS MA581, CAS CS237, ENG EK381, ENG EK500, or equivalen - Application of stochastic process theory to design and analyze algorithms used in statistics and machine learning, especially Markov chain Monte Carlo and stochastic optimization methods. Emphasizes connecting theoretical results to practice through combination of proofs, numerical experiments, and expository writing. Effective Fall 2023, this course fulfills a single unit in each of the following BU Hub areas: Writing-Intensive Course, Creativity/Innovation.

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