teaching

Workshop materials created for introduction into Data Science and programming languages

**This repository is currently under construction**

Teaching Repository

Author: Alex Nakagawa
This is a repository where all of the workshop and curriculum materials I have created reside. Most of these are in the form of Jupyter Notebooks and PDFs. You are free to do whatever you like with the materials that are in here.

Directory

[[decal-sql-lecture](https://github.com/alexnakagawa/teaching/tree/master/decal-sql-lecture)] - Introduction to PostgreSQL, SQL, and Relational Database Management Systems for the "Practical Data Science Skills for Internships" lecture series.
[[dss-intro-ml-workshop](https://github.com/alexnakagawa/teaching/tree/master/dss-intro-ml-workshop)] - Introduction to Machine Learning, with a focus on case studies, and how data scientists follow the data science lifecycle in the industry to approach certain problems.
[[dss-intro-r-workshop](https://github.com/alexnakagawa/teaching/tree/master/dss-intro-r-workshop)] - Introduction to using the R statistical programming language for data science. Created in collaboration with Junseo Park.
[[dss-python-ii-workshop](https://github.com/alexnakagawa/teaching/tree/master/dss-python-ii-workshop)] - Complete crash course on Python syntax with introductions to numpy and pandas for data science. Created in collaboration with Neelesh Dodda.
[[erg190c-hw8](https://github.com/alexnakagawa/teaching/tree/master/erg190c-hw8)] - Statistical analysis of environmental/geospatial data, CS189 topics.

External Teaching Resources

[[Data Science Modules Textbook](https://ds-modules.github.io/modules-textbook/intro)] - Lead an effort to consolidate Data Science Modules developed at UC Berkeley, co-edited by Shalini Kunapuli and Chris Pyles
[[PH 241: Statistical Analysis of Categorical Variables](https://github.com/PH241/materials)] - Graduate Course on Epidemiology. Created in collaboration with Nolan Pokpongkiat