This is a repository to house materials for a 2 day course introducing participants to data science using Python.
The goal of this workshop is to teach new-to-programming data professionals to import data, clean up and summarize a data set, and make some static data visualizations using Python. This is an introductory course to programming, specifically programming with Python. Python is a popular computer language for statistics and other scientific disciplines. It is commonly used for statistical analysis, machine-learning, generating high quality visualzations, and automating data workflows.
The workshop content will follow best practices for Python for data analysis, giving attendees a foundation in the fundamentals of Python and scientific computing.
Activity | Start Time | End Time |
---|---|---|
Session 1 | 9:00 | 10:30 |
Break | 10:30 | 10:45 |
Session 2 | 10:45 | 12:00 |
Lunch | 12:00 | 1:00 |
Session 3 | 1:00 | 2:30 |
Break | 2:30 | 2:45 |
Session 4 | 2:45 | 4:30 |
Important!
Before the course starts, we ask that all attendees install Python and its associated packages required for data analysis! Instructions for how to do so are found in the Introduction to Python Section. If anyone is having troubles getting Python up and running, please contact us before the course starts so that we can hit the ground running during the workshop.
To report bugs/issues/feature requests, please file an issue.
If you would like to contribute, please see our CONTRIBUTING guidelines.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
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