In my teaching, I aim to engage learners in a conversation about the material. I take care to practice the strategies for creating an inclusive computer science learning environment I learned in the Carpentries instructor Training.
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:::{grid-item-card} Computer Systems and Programming Tools
This is a new course that I designed to fill gaps identifies by students and
+++ course site, with syllabi by semester - current
course site - first iterations
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:::{grid-item-card} Machine Learning for Science and Society
+++ course site, with syllabi by semester
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:::{grid-item-card} Programming for Data Science
My key revisions to this course have been to:
- more code inspection
- more authentic tasks in assignments
- participatory live coding instruction
- mastery based grading
- more, smaller assignments
I also wrote a workshop paper on the design of the course
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course site, with syllabi by semester :::
:::{grid-item-card} Data & Society
a required course in the Brown University MS in DS
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:::{grid-item-card} Packaging and Publishing in Python
a lesson on how to organize, package, and document a python project in the Carpentries Incubator
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:::{grid-item-card} Software Carpentry Workshop at UCSF
I taught the python sections of the two day Software Carpentry workshop hosted by the UCSF Library March 10-11, 2018.
I used the SWC Python Gapminder curriculum with minor modifications to emphasize extra features of jupyter notebooks. I used github to manage the student downloads (by .zip files) and the final post workshop content and documented the process I used to for setup with this jupyter notebook.
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:::{grid-item-card} Bayesian Nonparametric Guest Lectures
I guest lectured in my PhD adviser Jennifer Dy's graduate machine learning course. I taught two lectures, the first introducing bayesian nonparamerics with the Dirichlet Process/ Chinese Restaurant Process and the second extending to the Indian Buffet Process.
Materials:
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