DataSci 217 is a practical introduction to the tools and reasoning used in Python data work. The course moves from the command line and Python fundamentals through NumPy, pandas, visualization, time series, modeling, and a complete question-led analysis.

Resources

• Canvas: https://canvas.ucsf.edu/courses/3010
• Lecture home: https://not.badmath.org/ds217
• Github: https://github.com/christopherseaman/datasci_217/

References (short list)

• Python for Data Analysis (rough basis for Python content)
• The Missing Semester (command line, git, data wrangling)
• The Linux Command Line book (command line in-depth)
• Tmux Fundamentals (free, beginner-friendly course)
• Markdown Guide (you can probably figure this one out)

See the library for more suggestions:

Reference Library

Development Tools (free!)

• VS Code (it’s pretty good)
• Python (great docs and tutorials, too!)
• GitHub Codespaces (IDE in a browser; free usage quota)
• Google Cloud Shell (practice command line anywhere)

WSL Troubleshooting

Course Format