Teaching
I teach a mix of data science and math courses Seattle University– my main emphasis is in the MS Data Science program. In all my classes, I place a strong emphasis on critical thinking, applying knowledge to real-world problems, and communication skills. I wrote an article in COMAP’s GAIMME Time (Guidelines for Assessment and Instruction in Mathematical Modeling Education) column about these goals.
If you teach similar courses and would like to share resources and ideas, please get in touch!
Courses
- DATA 5322: Statistical Machine Learning II
- DATA 5901 & 5902: MSDS Capstone series
- DATA 3310 & 5310: Data Visualization
- MATH 1335: Calculus II (Integral Calculus)
Teaching Resources
- QSIDE Data4Justice Curriculum
- Curriculum for data visualization using Altair, Python’s grammar of graphics plotting package
- An Introduction to Statistical Learning by James, Witten, Hastie and Tibshirani, a texbook for machine learning, available in R and Python
- The Craft of Community Engaged Teaching and Learning by Marshall Welch and Star Plaxton-Moore
- Laziness Does Not Exist by Devon Price, blog post and full book