class: title-slide # Teaching data science authentically using open source educational resources ### Tiffany Timbers, Dept. Statistics </br> University of British Columbia, Vancouver, BC --- ### Why create and use open educational resources (OER's) in general? -- - cost savings for learners 💸 -- - quick iteration and extension on materials for instructors ♻️ + 🏗️ -- - and raising the quality of the resources by facilitating collaboration 👥👥👥 -- - your teaching materials (and pedagogies) become more discoverable 🔍 --- class: middle ### Why create and use open educational resources in data science? ***All the reasons I just stated, and...*** ***... it mirrors the practices, tools and workflows used when practising data science***. --- class: center, middle ## Practice what you preach! --- class: middle ### Example of OER's we have built using data science open source tools 1. [*Data Science: A First Introduction*](https://ubc-dsci.github.io/introduction-to-datascience/) - an open textbook aimed at undergraduates students taking their first course in data science 2. [Syllabi, lecture notes, labs and lecture videos from courses for a professional Master's in Data Science program](https://github.com/UBC-MDS/public) 3. [Key Capabilities in Data Science online courses](https://extendedlearning.ubc.ca/programs/key-capabilities-data-science) - Interactive online learning modules aimed at mid-career learners --- ### *Data Science: A First Introduction* Aimed at first year undergraduates, from any discipline. .left-column[ <img src="img/dsci-100-team.png" width="50%" /> ] .right-column[ <img src="img/ds-first-intro-logos.png" width="90%" /> ] --- ### *Data Science: A First Introduction* .pull-left[ - Source code is available on GitHub: [github.com/UBC-DSCI/introduction-to-datascience](https://github.com/UBC-DSCI/introduction-to-datascience) - Created via R + `bookdown` R package. <img src="img/rmd-bookdown.png" width="30%" style="display: block; margin: auto;" /> ] .pull-right[ <img src="img/ds-first-intro-source.png" width="100%" /> ] --- ### *Data Science: A First Introduction* .pull-left[ - Book source and rendered HTML version openly licensed under [Creative Commons BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) and will remain that way indefinitely. - Partnering with CRC Press to publish and sell a print version. ] .pull-right[ <img src="img/ds-first-intro-license.png" width="90%" /> ] --- ### UBC MDS syllabi, lecture notes, labs & lecture videos Course resources from the UBC Professional Master of Data Science (MDS) program. .pull-left[ ##### Core (Past and present) MDS teaching team members - Tomas Beuzen - Vincenzo Coia - Giulio Valentino Dalla Riva - Mike Gelbart - Varada Kolhatkar - Rodolfo Lourenzutti - Firas Moosvi - Joel Ostblom - Alexi Rodríguez-Arelis - Tiffany Timbers *As well as several external faculty from the Departments of Statistics and Computer Science.* ] .pull-right[ <img src="img/mds-ubc-hex.png" width="75%" /> ] --- ### UBC MDS syllabi, lecture notes, labs & lecture videos .pull-left[ - Course resources from a Master of Data Science program: [github.com/UBC-MDS/public](https://github.com/UBC-MDS/public) - Program uses open educational resources from others, as well as creates its own - Syllabi and course notes created via Jupyter, R Markdown & hosted on GitHub <img src="img/mds-ubc-tools.png" width="90%" style="display: block; margin: auto;" /> - Videos of some courses hosted on YouTube ] .pull-right[ <img src="img/mds-oers.png" width="85%" /> ] *Instructors choose to share and distribute their resources using one of the available Creative Commons licenses.* --- ### *Key Capabilities in Data Science* online courses Online courses and certificate program, aimed at mid-career learners in BC, Canada (but open to anyone). UBC certificate program: https://extendedlearning.ubc.ca/programs/key-capabilities-data-science .pull-left[ - Course notes, videos and knowledge checks are openly available. - Paid version of the courses includes a course facilitator, office hours, graded assignments and quizzes. <img src="img/kccds-logos.png" width="85%" style="display: block; margin: auto;" /> ] .pull-right[ <img src="img/kccds-team.png" width="150%" /> ] --- ### *Key Capabilities in Data Science* online courses Open content created via Ines Montani's open course framework, whose front-end is powered by Gatsby and Reveal.js and back-end code execution is powered by BinderHub. - Python course starter pack: [github.com/ines/course-starter-python](https://github.com/ines/course-starter-python) - R course starter pack: [github.com/ines/course-starter-r](https://github.com/ines/course-starter-r) .pull-left[ <img src="img/course-starter-pack.png" width="80%" /> ] .pull-right[ Other online courses that use this framework (or a derivation of it): - [GAM's in R](https://noamross.github.io/gams-in-r-course/) by Noam Ross - [Supervised Machine Learning Case Studies in R](https://supervised-ml-course.netlify.app/) by Julia Silge - [Allen NLP Guide](https://guide.allennlp.org/) by Allen Institue for AI ] --- ### *Key Capabilities in Data Science* online courses <img src="img/joel-video.png" width="70%" /> --- ### *Key Capabilities in Data Science* online courses .pull-left[ <img src="img/mcq-exercise.png" width="68%" /> ] .pull-right[ <img src="img/code-exercise.png" width="68%" /> ] --- class: middle ### *Key Capabilities in Data Science* online courses | Course open content | Course source | |----|---| | [Programming in Python for Data Science](https://prog-learn.mds.ubc.ca) | [github.com/UBC-MDS/programming-in-python-for-data-science](https://github.com/UBC-MDS/programming-in-python-for-data-science)| | [Data Visualization](https://viz-learn.mds.ubc.ca/) | [github.com/UBC-MDS/exploratory-data-viz](https://github.com/UBC-MDS/exploratory-data-viz) | | [Introduction to Machine Learning](https://ml-learn.mds.ubc.ca/en) | [github.com/UBC-MDS/introduction-machine-learning](https://github.com/UBC-MDS/introduction-machine-learning) | *All content and source is openly licensed under Creative Commons Attribution 4.0 International ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/https://creativecommons.org/licenses/by/4.0/)).* --- ### Lessons learned from building, sharing and maintaining data science OER's -- - don't do it alone -- - don't be afraid to share works in progress -- - use a license -- - maintenance is needed to keep material current -- - interactive computation requires money and/or infrastructure --- class: middle ### Impact of our OER's at UBC so far - ~ 800 students have used *Data Science: A first introduction* as a free, online textbook - over 300 MDS students have completed MDS using primarily OER's - over 400 learners have taken the Key Capabilities in Data Science courses and used our open course content --- ### Resources #### GitHub for sharing teaching resources - [Creating a course repository to host materials on GitHub.com](https://ubc-dsci.github.io/jupyterdays/sessions/timbers/sharing-materials-with-git/sharing-materials-with-git.html#creating-a-course-repository-to-host-materials-on-github-com) - [Happy Git with R](https://happygitwithr.com/) #### Licenses - [About the Creative Commons licenses](https://creativecommons.org/licenses/) - [Choosing a Creative Commons license](https://creativecommons.org/choose/) #### Online book course resources - [How to write an open online book with `bookdown`](https://bookdown.org/yihui/rmarkdown/books.html#books) - [How to write an open online book with Jupyter book](https://jupyterbook.org/start/your-first-book.html) #### Online course resources - [Innes Montani's Python course starter pack](https://github.com/ines/course-starter-python) - [Innes Montani's R course starter pack](https://github.com/ines/course-starter-r) --- class: center, middle # Thank-you! Twitter: [@TiffanyTimbers](https://twitter.com/TiffanyTimbers) email: [tiffany.timbers@stat.ubc.ca](mailto:tiffany.timbers@stat.ubc.ca) slides: [bit.ly/timbers-jsm-21](bit.ly/timbers-jsm-21)