Introduction to Probability for Computer Scientists

Course Description

Topics include: counting and combinatorics, random variables, conditional probability, independence, distributions, expectation, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.

Course Details

Matriculated Stanford graduate students may enroll for 3, 4 or 5 units; everyone else must take the course for 5 units. All students do 5 units worth of work, including Stanford graduate students enrolled for 3 or 4 units.

Limited Enrollment Details: CS 109 is not open to High School Summer College or Horizon Scholar students. For a list of available Computer Science courses, please select "High School" or "Horizon Scholar" in the Student Population section of the Course page.

Prerequisites

CS 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.

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