CS109
Introduction to Probability for Computer Scientists
Computer Science
ENGR - School of Engineering
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.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
5
Course Repeatable for Degree Credit?
No
Course Component
Discussion
Enrollment Optional?
Yes
Course Component
Lecture
Enrollment Optional?
No
This course has been approved for the following WAYS
Applied Quantitative Reasoning (AQR), Formal Reasoning (FR)
Does this course satisfy the University Language Requirement?
No
Courses
CS109
is a
completion requirement
for:
CS109
is a
prerequisite
for:
Programs
CS109
is a
completion requirement
for: