Data Science at UCSB is a popular student-run club centered on developing career paths in the field of data science. The club offers resources, project experience and community to students from any major who are interested in data science.
The Data ANalysis and Coding Club (DANC) at UCSB is a new student group with the goal of establishing an inclusive community of beginning coders to develop professional skills for data science, computer modeling, and beyond.
Student Engagement and Enrichment in Data Science (SEEDS) is a Data Science Living and Learning community for UCSB students (including incoming Freshman and Transfer). This program draws the interest of prospective and current students that prioritize professional outcomes, small cohort-based learning, and opportunities for interdisciplinary and convergent learning. This is an opportunity for UCSB student populations to deeply understand and potentially make meaningful contributions in data science with goals to study ethics, how data is conceptualized and utilized in STEM, Social Sciences and Humanities. Our focus is to approach data science through workshops, conversations, mini lectures with a goal of integrating data science towards formal instruction in diverse disciplines. Visit the SEEDS website for more information, or to submit an application.
for Graduate Students
UCSB TidyTuesday is a weekly coding club where members practice their coding skills, share successes & challenges, and discuss all things data.
Eco-data-science is an environmental data science study group at UCSB "and beyond."
Openscapes is an approach for doing better science in less time. We offer mentorship and community engagement centered around open data science, helping teams develop collaborative practices that are more reproducible, transparent, inclusive, and kind.
The Research Data Services Department at the UCSB Library helps UCSB researchers manage and preserve their research data. Our team works with researchers throughout the research data lifecycle, from pre-project planning to post-project archival, and connect researchers with both locally- and externally-provided curation services. Our goal is to ensure that all research data is well-described and findable; accessible and reusable; citable; and sustainably preservable. Visit the website for a full list of services.
Carpentry @ UCSB aims to help researchers get their work done in less time and with less difficulty by teaching them basic research computing skills. Hands-on workshops will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. Workshops are free and typically half-day workshops in the mornings or afternoons. Topics taught can include Bash, Git, R, and/or Python. Click here for a list of past and upcoming Software Carpentry workshops at UCSB.
Data Science Instructional Computing Working Group seeks to simplify using browser-based Jupyter notebooks or R studio environments on the cloud for data sciences classes at UCSB. Additional information is available here (UCSB NetID is needed to view): Jupyterhub in the Classroom. Please contact Patrick Windmiller for more information and to start setting up a cluster for your class Members: Andreas Boschke, Ernesto Espinosa, Alexander Franks, Matthew Hall, Shea Lovan, B. S. Manjunath, George Michaels, Jeff Oakes, Sang-Yun Oh, Hector Villicana, Patrick Windmiller, and Yekaterina (Kate) Kharitonova.
R-Ladies Santa Barbara welcomes members of all R proficiency levels, whether you're a new or aspiring R user, or an experienced R programmer interested in mentoring, networking & expert upskilling. Our non-profit, civil society community is designed to develop our members' R skills & knowledge through social, collaborative learning & sharing. Supporting minority identity access to STEM skills & careers, the Free Software Movement, and contributing to the global R community! Google "R Ladies SB Meetup" for more information.