CS 109: Introduction to Probability for Computer Scientists
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.
Terms: Win, Spr

Units: 35

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Piech, C. (PI)
;
Sahami, M. (PI)
;
Agrawal, A. (TA)
;
Apostolatos, A. (TA)
...
more instructors for CS 109 »
Instructors:
Piech, C. (PI)
;
Sahami, M. (PI)
;
Agrawal, A. (TA)
;
Apostolatos, A. (TA)
;
Chen, M. (TA)
;
Eric, M. (TA)
;
Goodman, I. (TA)
;
Haaland, C. (TA)
;
Hsu, I. (TA)
;
Lin, W. (TA)
;
Luo, Z. (TA)
;
Martinez, P. (TA)
;
Nigam, P. (TA)
;
Puranik, A. (TA)
;
Rao, I. (TA)
;
Salloum, J. (TA)
;
Sun, Y. (TA)
;
Wang, D. (TA)
;
Weiler, A. (TA)
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