SML201 AI

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 Spring 2019. This course covers approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as for creating data products. The material covered also includes predictive modelling, R programming for data science, and the basics of statistical inference (random variables, sampling, probability distributions, parameter estimation, hypothesis testing, and linear regression.)

AIs are required to lead an 80-minute precept and to attend two course lectures (either Tu/Th 11-12:20 or Tu/Th 3-4:20) each week. Other duties may 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: Michael Guerzhoy
Appointment per precept: 3 hours
Requirements: Background in statistics; proficiency in R is an asset. We welcome applications from students in both technical disciplines and the candidates working with data in the social sciences.

Interested candidates should contact Michael Guerzhoy with a resume/CV, preferably before Jan. 1. Applications are accepted until all positions are filled.