For UC Berkeley Instructors
The Division of Data Sciences's Academic Resource Kit (ARK) for Instructors seeks to give instructors the ability to create and deploy educational materials in a variety of classes. The Division supports instructors in learning and incorporating data science approaches and teaching tools. We offer periodic workshops, summer trainings, and resources for course development.
Building from the freshman level, the Division of Data Sciences supports an open, interdisciplinary curriculum that stretches across campus and provides a foundation for Berkeley undergraduates of all majors to engage capably and critically with data. The Foundations of Data Science class (Data 8) is currently serving over 4,000 students per year across over 70 majors and fulfills statistics requirements in 90 percent of the majors that have one. More than 30 entry-level “connector” courses have been created by instructors in disciplines from humanities to engineering. Over 40 classes have deployed Data Science Modules adapted to enrich existingn classes. Instructors in many departments are now developing advanced courses in order to serve their existing majors, and to integrate with the major offered through the Division of Data Sciences.
Workshops & Resources
The Division offers a variety of opportunities to support instructors in learning and incorporating data science approaches, including workshops and programs to help develop course resources.
More information about workshops offered: https://data.berkeley.edu/news/data-science-education-opportunities
Data Science Modules - Request Development Support
Data science modules are short explorations that give students the opportunity to work hands-on with a dataset relevant to your course and receive instruction on the principles of data analysis, statistics, and computing. Modules vary widely and are customized based on each instructor’s objectives and the type of course, ranging in length from one to two lectures to multiple-session workshops culminating in a data-centered project. The Data Science Education Program provides assistance to instructors interested in adding data science modules to their existing classes, through student developer teams that partner closely with you to develop materials. A recent article and video explain how modules are currently being deployed.
For more information visit: https://data.berkeley.edu/education/courses/modules
Module Support Request Form: https://goo.gl/zRxVm7(link is external)
Proposals for Data Science Connector Courses (Fall or Spring)
Students in Data 8 learn computational and statistical concepts from a variety of examples spanning a broad range of disciplines. Connector courses (2, 3, or 4 units, often numbered 88) are designed to build on students’ analytical knowledge from Data 8 in connection to their own interests in a specific field. Connectors can be housed in a department, cross-listed in multiple programs, or piloted as a L&S course. The Data Science Education Program seeks to broaden the suite of connector offerings available to students and increase the potential to integrate data science into existing curricula. DSEP is able to provide a range of technical, pedagogical, financial, and community-building support to you in piloting a course, as well as computer lab space and lab assistants.
For more information visit: https://data.berkeley.edu/education/connectors
Data 8: Foundations of Data Science
Data 8 (data8.org)(link is external) is the flagship introductory Data Science class at UC Berkeley and is currently fully enrolled at more than 1,200 students every semester. The vision for the course is to combine teaching computational thinking and statistics, to modernize statistical instruction to center on statistical inference, and to be accessible to a broad range of students, including by eliminating requirements such as calculus, linear algebra, and introductory programming. Both programming and statistics are taught through Jupyter notebooks running Python.
Data 8x: An Online MOOC Implementation of Data 8 offered through EDx
Outside of Berkeley, this class is available as Data 8x, a popular course online at EDx. Several institutions have deployed Data 8 in a flipped classroom model, using the videos from EDx in combination with in-person lab help. edx.org/professional-certificate/berkeleyx-foundations-of-data-science(link is external)
The Data 8 textbook is at inferentialthinking.com(link is external). The textbook was written by John DeNero and Ani Adhikari and is licensed under a Creative Commons License. One of the key innovations of the textbook is that it has a set of Jupyter notebooks that provide programming illustrations of key concepts, which can be accessed at a local JupyterHub or more generally at mybinder.org(link is external). You can access the Jupyter Book repository at github.com/data-8/textbook(link is external); the README includes instructions for how to host/adapt the textbook at other sites and how to change the interact links.
The Data 8 homepage is at data8.org(link is external), where you can find the course sites for each iteration of Data 8 since fall 2015. Within the sites for past semester offerings, you can find slide decks and videos for lectures and Jupyter notebooks for in-class demos, as well as labs, homeworks, and projects. Almost all of the resources ( e.g., textbook, webpage, teaching materials) used for Data 8 are available the Github organization, github.com/data-8(link is external).
If you have questions about the Data Science Education Program in the Division of Data Sciences, feel free to contact us:
Cathryn Carson (firstname.lastname@example.org(link sends e-mail)), DSEP Faculty Lead
Eric Van Dusen (email@example.com(link sends e-mail)), DSEP Curriculum Coordinator