Institutional Resources, Foundations, Supports, Consolidation and Application of Undergraduate Data Science Education#
This book was produced with the support of the National Science Foundation (Grant #1915714).
Unique to the University of California, Berkeley’s Data Science Education development has been our DataHub Cyberinfrastructure and Autograding Cyberinfrastructure. The campus community enables full access to data science environments through any device capable of running a web browser connected to the internet. This alleviated the burden and inequity of requiring students to upgrade their personal computing devices to a minimum standard which would have been a barrier to widespread student participation. The autograder is an essential component of any scalable computation-centered course that includes graded assignments. Otter Grader is used for autograding.
The Data Science Undergraduate Studies program at UC Berkeley is a matrix of courses and learning opportunities for students to be directly involved in Data Science both in and outside of classrooms. UC Berkeley’s most notable Data Science development has been the creation of the Data Science major and minor programs that welcomes a large number of students from diverse academic and personal backgrounds. The Foundations of Data Science Course, Data 8 serves as an initial access point for many students who are interested but might not have any prior experience. Students may initiate their Data Science experiences through this course or find their way to Data 8 from Data Science Modules, known as “Modules” that have been embedded into the curriculum of other domain area courses. The curricular experiences of students may then continue both through upper level Data Science courses and through Domain Connector Courses, or better known as just “Connector Courses” that integrate Data Science learning across the semester-long course. The Data Science Discovery Projects also offers students the opportunity for applied experience with partnering organizations on a semester-long project.
Conscious of the differences in student experiences and backgrounds, programs continue to be developed that focus on uplifting and providing additional support to students from populations that are underrepresented in Data Science.
The Data Scholars Program accepts a cohort of students each semester for participation in the program components: a foundations seminar, academic development, discovery research, career accelerator, and a speaker series. The Data Scholars Foundation Seminar is a course that provides additional structure and support as they are enrolled in the Foundations of Data Science Course. The Data Scholars Pathways Seminar invites students to join in a series of talks from professionals in the field to learn more about career opportunities and development. The Data Scholars Discovery Research Projects partners with the existing Discovery Research Program to ensure Data Scholars are matched with appropriate research projects for a semester-long experience.
Transfer Mentors is a newly established program (2020) that is continuing to develop and build capacity for entering transfer students interested in Data Science through direct support by current more established transfer students.
Students looking for additional hands-on learning experiences in courses and with peers might become involved in a number of employment opportunities.
Students can assist in the development of the course content for Modules as part of a Modules Jupyter Notebook Developers or the Jupyter Notebook Development Team.
They might assist peers through direct 1:1 conversations through the Data Peers Consulting program.
Students can become part of the teaching staff for the Introduction to Data Science course, Data 8, the Foundations Scholars or the Discovery Scholars; they can become an Undergraduate Student Instructor or a tutor.