Our Courses
The Learning Hub maintains a collection of expert data science learning materials, programs and more. Get familiar with and find resources on:
coreR | OpenS | Customized Training | Director's Scholarship
Courses & Materials
Since its inception, NCEAS has developed intensive data science courses for researchers from any discipline or sector. We are pioneers in collaborative science, and leaders in data science management and software development - these are the pillars of our curriculum.
We work in collaboration with our partners to develop course content; from Open Science for Synthesis for Alaska salmon researchers to advanced computing for Arctic scientists. See below the materials we offer and how to get started.
coreR
Course description
coreR is a 5-day in-person immersion into R programming and data management with a focus on environmental data science. Throughout the course, researchers gain experience using essential data science tools and learn best practices for collaborative, reproducible, and open science.
Topics include:
- Introduction to R programming
- Tidy data and data wrangling
- Writing functions and packages
- Data management
- Version control using Git & GitHub
- Data management plans and metadata
- Reproducibility
- Data visualization
- Literate analysis using Quarto
- Publishing to the web
- & more!
Learn more and register for the upcoming course>>
This course is taught in partnership with DataONE.
What are these courses:
The Arctic Data Center offers three courses for Arctic researchers with the overall goal of providing these specific researchers the critical skills needed to be stewards of arctic data, software, and other research products maintained by the NCEAS-operated Arctic Data Center. These courses are taught both in-person and virtually.
Who should attend:
- Must be an Arctic researcher to attend.
- Each course has their own prerequisites, but familiarity with R programming basics is necessary for the Fundamentals and Reproducible courses; and familiarity with python programming basics is necessary for the Scalable course. Reach out to training@arcticdata.io for more information and pre-course preparation recommendations.
Available courses:
- Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
- Reproducible Practices for Arctic Research Using R
- Scalable and Computationally Reproducible Approaches to Arctic Research
Overall Learning Goals:
- Utilize best data management practices and data sciences tools for Arctic research.
- Employ methods for documenting and uploading data to the Arctic Data Center.
- Effectively manage large datasets.
Registration details: Apply on the Arctic Data Center website.
Cost: Free for Arctic researchers.
Questions? Email training@arcticdata.io.
Apply for the next training session >>
Support for these courses and its participants is provided by the National Science Foundation.
What are these workshops:
Master of Environmental Data Science (MEDS) Workshops are developed for MEDS students and are meant to supplement MEDS curriculum and teach additional skills. Workshops are only open to MEDS students and sometimes the wider UC Santa Barbara community, but all materials are open source and available to view online after the workshop.
Who should attend: Must be a current MEDS student to attend
Available workshop materials:
- An Intro to Cloud Computing for Data Science
- Creating Your Personal Website Using Quarto
- Customizing Quarto Website: Make your website stand out using Sass & CSS
- Customizing Your Personal Website with CSS
- Data Science Blogs: How to start one, and what to write about
- Demystifying the Technical Interview
- IDE Tips & Tricks
- Intro to Shiny
- Programming with Python & Intro to Webscraping
- Relational Databases and SQL
- Teach Me How to Google
- Writing Data Science-Related Blog Posts for your Personal Website
- and more!
Questions? Email academics@bren.ucsb.edu
What are these resources:
The Data Management Skillbuilding Hub is a repository of teaching and learning materials on data management topics across all stages of the Data Life Cycle.
Who these resources are for:
Initially, DataOne worked in collaboration with the community to develop resources for educators and librarians leading data management trainings. Today, the resources are for all who are interested in teaching or learning best data management practices.
How to contribute:
The Skillbuilding Hub is open source and maintained by the community. To contribute please review the contributing document on GitHub.
Topics of available materials:
- Analysis and workflows
- Data citation
- Data entry and manipulation
- Data management planning
- Data sharing
- Legal and policy issues
- Metadata
- Protecting your data
- Quality control and assurance
- Why manage data
Questions? Open an issue in the DateONEorg Education repository on GitHub.
What are these webinars:
DataOne webinars began in 2015 as monthly discussions on open science, the role of the data lifecycle, and achieving innovative science through shared data and ground-breaking tools. The webinar series is currently on pause.
Who are these webinars are for:
Everyone and anyone interested in open science, the data lifecycle, and data science generally!
Questions? Email support@dataone.org
coreR
Course description
coreR is a 5-day in-person immersion into R programming and data management with a focus on environmental data science. Throughout the course, researchers gain experience using essential data science tools and learn best practices for collaborative, reproducible, and open science.
Topics include:
- Introduction to R programming
- Tidy data and data wrangling
- Writing functions and packages
- Data management
- Version control using Git & GitHub
- Data management plans and metadata
- Reproducibility
- Data visualization
- Literate analysis using Quarto
- Publishing to the web
- & more!
Learn more and apply to coreR here!
Open Science for Synthesis (OpenS)
Course Description
Whether you’re just starting out in your research career or you’re looking to deepen your expertise, this hands-on course offers valuable data science skills. This course was designed for both early-career researchers and established professionals seeking to enhance their skills in science synthesis, reproducible science, and data management.
In 2013, 2014, and 2017, participants came to NCEAS for three weeks of extensive training in scientific computing and software with a focus on reproducibility. This page archives the course format and materials from these training sessions.
Course Topics
The training focuses on scientific computing and software tools for reproducible research. Instructors emphasize integrating statistical analysis into well-documented workflows, using open-source, community-supported programming languages such as R and Python. Participants gain practical skills for quickly and reliably implementing open-source scientific software with applications to ecological, environmental, and evolutionary Earth, and marine science synthesis.
Throughout the course, participants work on group synthesis projects following these core themes:
- Collaboration modes and technologies, including virtual collaboration
- Data management, preservation, and sharing
- Data manipulation, integration, and exploration
- Scientific workflows and reproducible research
- Sustainable software practices
- Data analysis and modeling
- Communicating results to diverse audiences
The course provides a solid foundation in the computing skills needed for synthetic research in today’s computationally- and data-intensive era. These topics include:
- Instruction in programming languages like R and Python for data manipulation, analysis, and visualization
- Analytical methods for synthesis research, such as meta-analysis and systematic reviews
- An overview of general programming principles, paradigms, and best practices
- Exposure to the Linux/UNIX command line environment and essential tools
- An introduction to the underlying technology of modern computing and its relevance to scientific research
- Discussions on cyberinfrastructure trends supporting open, reproducible science
Is OpenS the right fit for your team?
Learn more about collaborating with NCEAS and hosting your trainings events with us here.
Explore previous OpenS courses here.
Funding details:
The Director's Scholarship is applicable to only the coreR course. We are able to offer scholarships for in-person coreR courses.
Award recipients for an in-person course will receive a tuition waiver ($1,700), plus reimbursement for travel, lodging, and per diem for the entire length of the course (five days). Travel and lodging must be reserved through NCEAS' travel coordinator. At this time, we are only able to fund in-person courses for participants who currently reside in the United States.
Application details:
The scholarship application must be completed online and includes four short essay questions (max 250 words for each question). We recommend preparing your answers before opening the application since you will not be able to save your progress during the application or edit after submitting. See essay questions below:
- In the spirit of expanding the opportunity to a broader applicant pool, we are providing funds to support up to two applicants per virtual training and one applicant per in-person training. If you are currently funding by a NSF or other grant or if you have funding from your employer/advisor/institution, we ask that you first look for eligible support. Please explain your rationale for requesting funding. (250 words)
- What impact will attending this course have on your career and your scientific and/or social communities? (250 words)
- Have any circumstances in your personal and/or professional life presented barriers to your participation in environmental science and/or data science? (250 words)
- We would also like to provide the opportunity for you to share any experience you have working towards diversity, equity, and inclusion in environmental science and/or data science. (250 words)
Questions? Email deij@nceas.ucsb.edu.
The Individualized Professional Skills (IPS) Program
Funding details: Awards up to $1000 available for UCSB graduate and postdoctoral scholars to pursue professional development opportunities.
Application details: Must be completed online and includes information about yourself and your Individual Development Plan mentor, proposed opportunity, itemized estimated budget, and and two essay questions.
Questions? Visit IPS Program website >>
Dilling Yang's Staff Scholarship
Funding details: Awards up to $500 (other amounts may be considered) for non-probationary career staff with a full-time-equivalent salary less than or equal to $5,870 per month to pursue professional development opportunities. Awards can only be applied toward registration and educational fees for learning opportunities offered at UCSB only.
Applications details: Must be completed online and includes information about yourself, learning opportunity, and one justification essay question.
Questions? Visit UC Santa Barbara Extension Professional and Continuing Education website >>
Customized Training
NCEAS aims to share our decades of experience in leading synthesis science with others. And as researchers ourselves, we know data science needs vary from group to group. Keeping these notions in mind, NCEAS offers fee-based training for groups that can be custom built to fit specific needs and are founded on team science principles. Training can be delivered on-site or virtually.
We've been providing data support and teaching collaborative science to LTER synthesis working groups and others for 27 years and counting. We have developed a plethora of resources including guides, ad hoc trainings, and hands-on computing support. Reach out to us at learning-hub@nceas.ucsb.edu to set up a customized training for your group. To get a sense of what a customized training could look like, see below for examples of materials and services we provide.
Available resources for Working Groups:
- How to Run a Working Group
- Computing Support
- Communications Resources
- and more!
Training materials topics:
- Open Science for Synthesis
- Reproducible analyses in R
- Collaborative version control using git and GitHub
- Data management and documentation
- Ethical data science principles such as FAIR and CARE
- and more!
All training materials are archived on the NCEAS GitHub.
What the Scientific Computing Team does:
- Provide modern technological infrastructure to support analytical, computing, or network-based needs for LTER synthesis working groups.
- Workshops, Tutorials, and Coding Tips in R programming and on R-based data science tools.
Community & Events
A key aspect to synthesis science is building community and providing events for data scientists to come together. We love the data science community and we want everyone to have a welcoming experience and sense of belonging when engaging with it.
That's why at NCEAS, we've developed and maintained multiple community efforts. Get to know some of the communities we've developed or partnered with below, and get involved!
Find your place in the data science community.
What it is:
The Environmental Data Science (EDS) Summit aims to bring together all types of environmental data scientists to lay the foundation for a more cohesive and collaborative transdisciplinary community. Its primary goals are to build community and foster collaboration within the EDS community. The 2023 theme is Harnessing Diversity in Environmental Data Science.
How to participate: Apply online.
Learn more about the Environmental Data Science Summit >>
Applications for the 2023 EDS Summit are now closed. Join the listserv to stay up to date!
What it is:
EcoDataScience is a data science community created by environmental scientists, students and researchers who want to learn together. They support data science learners through:
- Skill Sharing
- Co-working
- Community Building
How to participate:
- Open an issue on the eco-data-science GitHub repository
- Join on Slack or the Google Group
UCSB Data Science Initiative
What is it: Campus initiative to support a broad spectrum of campus data science goals.
How to participate: Reach out to a research group, attend an upcoming event, get a consult, attend the Data Science Summit, and more.
Learn more on the UCSB Data Science Initiative website >>
The Research Data Services Department
What is it: RDS operates out of the UCSB Library and helps researchers manage and preserve data.
How to participate: Connect with the RDS Dept for a consultation and to learn about their services.
Learn more on the Research Data Services website >>
Carpentry @ UCSB
What is it: The Carpentries project is an international organization of volunteers teaching foundational coding and data science skills to researchers. Carpentry Workshops at UCSB are supported and organized by our stellar volunteers and the DREAM Lab at UCSB Library.
How to participate: Attend a workshop, event or community meeting.
What it is:
Openscapes is an approach to science that is more efficient and collaborative, and can uncover environmental solutions faster. They provide mentorship and community engagement services centered around open data science, helping teams develop collaborative practices that are more reproducible, transparent, inclusive, and kind. Openscapes was incubated by NCEAS and a Mozilla Fellowship awarded to Julia Stewart Lowndes.
How to participate:
- Join their mailing list
- Attend an upcoming event
- Take part in the Champions Program
What it is:
The Santa Barbara Chapter welcomes members from all levels of R proficiency and from all sectors. They host regular gathering of women, minority identities, and allies to network and develop skills in R programming. R-Ladies Santa Barbara is a local chapter of the global R-Ladies organization, and the chapter was founded by two of resident NCEAS data scientists.
How to participate:
- Join the Meetup group
- Attend an upcoming event
- Review past presentation materials on GitHub
- Give a talk!