The PhD Years

Graduate School Coursework

I maintain a list of courses I’ve taken in the time I’ve spent in graduate school at UC Berkeley. For each course listed, names of instructors are given in parentheses, wherever appropriate.

Before Graduate School

Before starting graduate school officially, I completed a small number of graduate courses during my undergraduate years at UC Berkeley. Many of these courses were foundational in helping me find my way into and through the Biostatistics PhD program. Here is a list of those courses:

Fall 2016

Spring 2017

Fall 2017

Spring 2018

  • Computational Biology 293: Doctoral Seminar in Computational Biology (Nir Yosef)
  • Statistics 260: Observational Study Design and Causal Inference (Sam Pimentel)
  • Public Health 290: Biomedical Big Data Training Program Capstone (Mark van der Laan & Alan Hubbard)

Fall 2018

Spring 2019

  • Statistics 210B: Theoretical Statistics (Michael Jordan) [auditing]
  • Statistics 215B: Statistical Models: Theory and Application (Jon McAuliffe)
  • Statistics 260: Probabilistic Modeling in Genomics (Yun Song)
  • Public Health 290: Current Topics in Causal Inference (Maya Petersen)
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Nima Hejazi
Biostatistics PhD candidate

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