CS145, Fall 2018, taught by Professor Eli Upfal

Probability and statistics have become indispensable tools in computer science. Probabilistic methods and statistical reasoning play major roles in machine learning, cryptography, network security, communication protocols, web search engines, robotics, program verification, and more. This course introduces the basic concepts of probability and statistics, focusing on topics that are most useful in computer science applications. Topics include: modeling and solution in sample space, random variables, simple random processes and their probability distributions, Markov processes, limit theorems, and basic elements of statistical inference.

This course emphasizes both mathematical rigor and computing applications. Topics are similar to Statistical Inference I (APMA 1650) with more of a focus on modern applications and formal proof.

Course registration is currently full; please fill out this form to be added to the waitlist. The waitlist will be resolved after grading of the first homework (within the first week of class). We expect all students who perform well on the first homework to be successful in the class.

If you have any questions about the course, please email the HTA Zack.

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