Thread by @Tomdonoghue

New Educational Materials for Learning Data Science:

We've created a public online resource for our Python based course "Data Science in Practice".

Materials include tutorials, guided assignments, and project guidance. (Additional info below).

Webite:
datascienceinpractice.github.io

This is work with @bradleyvoytek, who created this course, and @Shannon_E_Ellis who teaches and develops it. (I have worked on course materials & the site).

Thousands of students have taken this course at UC San Diego, and now we're making the materials more openly available.

The premise of this course is to be a guide to the hands-on and practical elements of doing data science. It digs into the day-to-day of data practice, designed to be a complement to more technically in-depth courses in statistics and machine learning.

The materials focus on introducing and briefly describing key topics, offering code examples and guided practice, and linking out to more in depth resources. We hope they serve as something of a "map" for the many other resources available across topics in data science.

Specifically, the website includes:
- Tutorials: hosted notebooks that introduce key topics
- Assignments: downloadable, guided example assignments to practice skill
- Projects: a description of how we ask students to pursue independent data science projects

It's also a work in progress, and we're still working on making sure these materials are usable & useful outside the context of the full course.

If you have any comments / suggestions, please let us know!

You can do so on Github at the host repository:
github.com/datascienceinp…

Of course, these materials are only possible because of the open-source ecosystem for data science & pedagogy.

Materials are built with Jupyter notebooks and tooling from @ProjectJupyter. The website is hosted using Jupyter-book, developed by @choldgraf & team. (Thanks to all!)

I hope these materials are useful!

Please check them out, try them, share them, adapt them if you want (they are licensed CC-BY-NC), and use them however works!

Let us know if they are useful and/or what could be updated!

/end

Website link again:
datascienceinpractice.github.io