On university campuses around the world, students and researchers see the potential benefits of applying natural language processing methods to their work. For many, acquiring these skills can be a difficult, unintuitive and intimidating experience.
I want to change that. I’m passionate about making NLP accessible to everyone, especially those who don’t (yet) have backgrounds in computer science or mathematics.
As the Python and NLP lead at D-Lab, I lead a team who design, create and teach workshops. Some of the workshops I’ve taught include:
- NLP with Python
- Computational text analysis
- Data wrangling with pandas
- Version control with Git and GitHub
- Regular expressions
- Python fundamentals
Previously, I was an advisor for DS modules, a student-led program that creates short forays into data science in existing domain courses (e.g. Sociology, Gender Studies, Psychology). The goal is to show students how data science skills can be applied in their field. If you’re teaching a course at Berkeley and are interested in having a module for your class, please fill out this form.
I am a co-instructor for a number of MOOC courses for SAGE campus, including:
- Introduction to data science for social scientists
- Data science with Python
- Text analysis
- Data visualization
- Machine learning
- Network analysis
- Cleaning data and preprocessing
In the summer of 2016, I taught Berkeley’s introductory cognitive science course. As a GSI, I’ve taught a seminar on language and thought as well as courses on language acquisition with Mahesh Srinivasan, introductory linguistics with Larry Hyman and introductory cognitive science with Terry Regier.
In 2014, I was the non-resident tutor for Arabic and phonetics at University College, one of the ten residential colleges at the University of Melbourne.