This repository is a set of tutorials for learning data science, created as part of the Data Science in Practice class.

These materials are also publicly available and hosted online at datascienceinpractice.github.io/.

These tutorials are designed to be an introduction to data science.

The goal is to offer hands-on materials that allow for getting started with finding and analyzing data, in order to build up to working on data-science related projects.

These materials are in the Python programming language, and presume basic knowledge of programming and standard library Python.

These tutorials also try to interface with the vast world of existing tutorials, materials, and documentation. They are explicitly designed to give a quick introduction to a topic of interest, and then link out to more comprehensive resources. In that sense, they are designed to be more like a yellow pages than an encyclopedia.

The code and materials in this repository are created with Jupyter notebooks and require the anaconda distribution. Any other dependencies, for specific Tutorials, are specifically addressed in the notebooks.

This repository is developed and maintained by TomDonoghue, as well as by the COGS108 staff.

Contributions to this resource are welcome and encouraged! If you have suggestions for new links or materials, and/or fixes for any issues you spot, you are welcome and invited to open Issues, and/or submit a Pull Request.

These materials are made freely available, and are licensed under a CC-BY 4.0 license.