This page contain advice, resources, etc on designing and running a project-based course. At the top are links to various blog posts that you might find useful for designing such a course. Below that are a set of peer-reviewed resources and other useful links/resources. Please feel free to contact me with questions or for more detailed course materials.


Advice for Project-Based Courses

Version Control and Reproducible Research/Data Science (this also has some more project templates)

Resources for Learning Data Science Visualization


Non-Peer Reviewed Resources

From Tiffany Barnes @ NC State University:

A project outline for semester-long projects. https://goo.gl/opUWX2


I have modified Tiffany’s outline somewhat to reflect a bit better the “Data Science” life-cycle, specifically adding a “Data Preprocessing” and a “Algorithm Plan” stage. This is still a work-in-progress as I teach with it. Feel free to leave comments if you use it and find issues. 

https://goo.gl/Ypj3Da


A presentation by Lisa Dierker @ Wesleyan University, “Reaching Students with Passion-Driven, Project-Based Statistics”

https://www.causeweb.org/cause/webinar/teaching/2013-06/


Potential Data Science Project Templates (for cloning):

From Microsoft, primarily ‘R’ based: https://github.com/Azure/Azure-TDSP-ProjectTemplate

From “Cookie-Cutter Data Science”, primarily ‘Python’ based: https://drivendata.github.io/cookiecutter-data-science/    


Here are several project/process life-cycle diagrams that can help frame the entire project also:

Microsoft’s “Team Data Science Process” (TDSP) life-cycle

Cross Industry Standard Process for Data Mining (CRISP-DM)

Knowledge Discovery in Databases (KDD)


I’ve also found that Microsoft’s “Beginner’s guide to Data Science” does a really excellent job of summarizing quickly the types of questions a project might entail… (all 5 of their videos are pretty good for a total of about a 25/30minute intro)

https://docs.microsoft.com/en-us/azure/machine-learning/studio/data-science-for-beginners-the-5-questions-data-science-answers


How Carnegie Mellon University-Information Systems (CMU-IS) describe partnership offers to potential clients:  http://www.cmu.edu/information-systems/client-partner/

Show-case of past (CMU-IS) projects: http://www.cmu.edu/information-systems/showcase/

Project-Based Capstone from Computer Science & Engineering at Michigan State University (other years by modifying the URL): http://www.capstone.cse.msu.edu/2018-01/home/


A very alternative (and a bit perhaps a bit less data-centric idea for now) — Humanitarian Free and Open Source Software (HFOSS). This could also be an interesting avenue for developing relevant introductory data-science project courses. (Provided by Heidi Ellis @ Western New England University (WNE) )

About HFOSS Projects: http://foss2serve.org/index.php/POSSE
Sample Activities/Projects: http://foss2serve.org/index.php/Learning_Activities


Help Finding Projects (maybe): Riipen — https://riipen.io

Riipen is a Canadian based company that supposedly helps find (and mediate) experiential learning opportunities for students. I’m using it this semester to manage my projects in Data 151: Introduction to Data Science … however they didn’t actually find me any projects (so the real hope of less work didn’t materialize).

Peer-Reviewed Sources

Articles from the Journal of Statistics Education:
(Thanks to Michael Posner @ Villanova for this list, via the SIGCSE list-serv)


From SIGCSE Proceedings:
(Thanks to Joseph Mertz @ Carnegie Mellon University for these links)


Do you have other good articles to recommend (from other journals?) Please send them along to me and I’ll happily post them!

Also, if you have any trouble with bad links (or don’t have access to the articles) please let me know so I can fix them or help you.