Data Science Curriculum Development, UC Berkeley
As a part of my time at the Division of Data Sciences at UC Berkeley, I participated in curriculum development for some courses that are taught by Division staff and for other “data-enabled” courses (courses outside the Division but which use Division infrastructure). The first course that I worked on, L&S 88, focused on reproducibility and open science. It was a connector course for Data 8 (the foundational course for data science students) and it was my role as a connector assistant that spurred me into working more and more at the Division.
I present here some of the materials that I developed for courses at UC Berkeley as a part of the work I did at the Division, as well as some details on the courses they are for and my role therein. Most of what I present here is work relating to curriculum development, but I also worked as something of a lab assistant on courses, including L&S 88.
Spring 2019. This course was a Data 8 connector course that focused on questions of reproducibility and open science within the Data Science community. It featured lectures on things like Project Jupyter, Licensing, and Data Repositories & Archiving. My role in this class was as a connector assistant, which primarily involved curriculum development and lab assisting in class. I developed quite a few labs for this course, including a
matplotlib tutorial and a lab on Python vs. R in Jupyter notebooks