Princeton University
Center for Statistics and Machine Learning - SML 201 AI

The Center for Statistics and Machine Learning at Princeton University has openings for AIs to teach

precepts for SML 201 during the fall and spring of the 2018-2019 academic year. This course covers

approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as creating

tools based on data. In addition, it includes concepts such as random variables, sampling, probability

distributions, estimations, hypothesis testing, and regressions, as well as relevant computational


AIs are required to lead a precept (50-minute, TBD) and to attend two course lectures (either Tu/Th

11-12:20 or Tu/Th 3-4:20) each week. Other duties include: designing precept materials, writing up

project and problem set solutions, grading, answering technical questions, weekly meeting with the

course instructor, and holding regular office hours.


Instructor: Daisy (Yan) Huang

Appointment per precept: 2 hours

Requirements: Background in statistics is required; Proficiency in R is an asset

Interested candidates should contact Daisy Huang

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