Content from the University of British Columbia's Master of Data Science course DSCI 511.
By Tomas Beuzen 🚀
Welcome to Python Programming for Data Science! With this website I aim to provide an introduction to everything you need to know to start using Python for data science. We'll cover topics such as data structures, basic programming, code testing and documentation, and using libraries like NumPy and Pandas for data exploration and analysis.
If you're interested in learning more about Python packages, check out my and Tiffany Timber's book Python Packages. Or, if you'd like to learn more about using Python and PyTorch for deep learning, you can check out my other online material Deep Learning with PyToch.
The content of this site is adapted from material I used to teach the 2020/2021 offering of the course "DSCI 511 Python Programming for Data Science" for the University of British Columbia's Master of Data Science Program. That material has built upon previous course material developed by Patrick Walls and Mike Gelbart.
These are the key learning outcomes for this material:
The material on this site is written in Jupyter notebooks and rendered using Jupyter Book to make it easily accessible. However, if you wish to run these notebooks on your local machine, you can do the following:
git clone https://github.com/TomasBeuzen/python-programming-for-data-science.git
conda env create -f py4ds.yaml
cd python-programming-for-data-science
jupyterlab
If you're not comfortable with
git
,GitHub
orconda
, feel free to just read through the material on this website - you're not missing out on anything!