2026 Data Science in the Classroom Conference
Data Science in the Classroom (DSC) Conference
July 24, 2026
Riverside City College
Who Should Attend?
- Community college and university faculty, researchers, and administrators
- K–12 educators
- Curriculum developers and educational leaders
No prior experience teaching data science is required.
Community Conversations
Community Conversations are designed to explore, initiate, and facilitate grassroots efforts to shape data science education in Southern California and beyond. Participants will collaborate to identify common challenges, discuss potential solutions, and (we hope) take away actionable next steps.
Themes
Community Conversations are an opportunity to share your voice about the present and future of data science education.
Community Conversations at DSC 2026 are currently scheduled around the following themes:
- Sustaining the Community of Data Science Learners
- Strengthening Data Science Pathways through Articulation
- Incorporating Data Science in Traditional Courses: Modules and Beyond
Featured Speakers
Insight and Impact in the Field of Data Science
Dr. Louis Ehwerhemuepha, Director, Research Computational and Data Science, Rady Children’s Health Orange County
Louis Ehwerhemuepha, PhD is the Director of the Research Computational and Data Science (Computational Research) team at Rady Children’s Health in Orange County (formerly CHOC). He leads a multidisciplinary team of data scientists and statisticians focused on advancing pediatric research through the application of statistics, machine learning, and artificial intelligence. Under his leadership, the team applies methods ranging from statistical learning on structured electronic medical record (EMR) data to deep learning approaches for computer vision and natural language processing in pediatric medicine, while also providing research data science support across the health system.
Dr. Ehwerhemuepha’s applied research spans a broad range of clinical and population health domains, including hospital readmission, sepsis, COVID-19, artificial intelligence for rare diseases, population health management, and the care of children with complex chronic conditions, particularly neurological and cardiovascular disorders. He has led the deployment of multiple statistical and machine learning models into the EMR, contributing to measurable improvements in quality of care. He collaborates closely with University of California, Irvine faculty in Pediatrics, Statistics, and Data Science to address clinically meaningful problems and advance pediatric health outcomes.
Transforming the Landscape of Data Science Education
Caroline Hutchings, Professor of Mathematics and Data Science, Norco College
Caroline Hutchings is a Professor of Mathematics and Data Science at Norco College and a leader in expanding access to data science education across the Inland Empire. She earned a Master of Data Science from the University of California, San Diego, a Master of Statistics from the University of Utah, and a bachelor’s degree in Psychology and Mathematics from the University of Utah. At Norco College, she has been instrumental in developing the college’s data science program, including creating a data science associate degree, building transfer pathways, and launching dual-enrollment data science courses for high school students.
Professor Hutchings serves as Co-Principal Investigator on the NSF-funded DS-PATH: Data Science Career Pathways in the Inland Empire project and has contributed to numerous regional and national initiatives, including Greater LA Data Science Pathways (GLADS-PATH) and Project PIPE-LINE. She is deeply committed to broadening participation in STEM and data science through student mentoring, industry partnerships, research opportunities, conference engagement, and peer-support programs. Through her leadership in curriculum development, faculty collaboration, and workforce pathway initiatives, she is helping transform the landscape of data science education and preparing students to thrive in an increasingly data-driven world.
Educator-Driven Curriculum Innovation in Data Science
Dr. Ji Son, Professor of Psychology, California State University, Los Angeles, and Co-Founder, CourseKata
Ji Y. Son is Professor of Psychology and Director of the Learning Lab at California State University, Los Angeles. She co-authored Statistics and Data Science: A Modeling Approach (CourseKata.org), an interactive textbook used at more than 150 institutions by over 35,000 students. Her research examines how insights from the learning sciences can improve teaching and learning at scale, particularly in mathematics, statistics, and data science. She studies how to design learning environments that help students develop understanding that endures even as data and artificial intelligence reshape the world around them. Across her research, curriculum design, and teaching, Ji is guided by a simple idea: learning changes the way we see the world.
Featured Panel: Student Voices in Data Science
A featured student panel will highlight the experiences of Norco College students who have participated in data science coursework, internships, hackathons, research projects, and conferences. Students will share how these opportunities have influenced their academic journeys, career aspirations, and transfer goals.
Hands-On Workshop: Open Source Curriculum and Interactive Computing Workflows
This interactive workshop introduces participants to UC Berkeley’s nationally recognized Data 8 curriculum and the open-source tools that support large-scale data science instruction. Attendees will explore course materials, assignments, Jupyter-based computing environments, and instructional workflows that can be adapted for their own classrooms and institutions.
Edwin Vargas Navarro is a member of the Data Science Undergraduate Studies (DSUS) team at UC Berkeley, where he supports the adoption of UC Berkeley’s data science curriculum and instructional modules at colleges and universities. He has taught introductory data science courses and is passionate about expanding access to high-quality data science education. Edwin enjoys collaborating with educators to advance data science instruction and looks forward to engaging with participants and learning about their innovative work.
Schedule
| Time | Event |
|---|---|
| 8:00-8:30 | Registration and Networking Breakfast |
| 8:30-9:15 | Opening Remarks |
| 9:15-10:15 | Insight and Impact in the Field of Data Science |
| 10:15-10:30 | Break and Refreshments |
| 10:30-11:30 | Transforming the Landscape of Data Science Education |
| 11:30-12:00 | Student Voices in Data Science: Pathways, Opportunities, and Impact |
| 12:00-1:00 | Lunch |
| 1:00-2:00 | Community Conversations |
| 2:00-2:15 | Break and Refreshments |
| 2:15-3:15 | Educator-Driven Curriculum Innovation in Data Science |
| 3:15-3:45 | Creating Sustainable Pathways in Data Science - The UC Berkeley Data 8 Ecosystem |
| 3:45-4:00 | Closing Remarks |
| 4:00-6:00 | Hands-On Workshop: Open Source Curriculum and Interactive Computing Workflows (Optional) |
A more detailed agenda is now available.
Continue the Conversation
Our online Community of Data Science Learners web forum continues the conversations in a friendly, organized way. Post with the tag #DSC2026 to highlight the major insights you came away with, or reply to what others took away from the conference. No social media or app necessary!
About the DSC Conference
As data literacy becomes increasingly important across disciplines and careers, educational institutions must adapt to prepare students to thrive in a data-driven world. The Data Science in the Classroom (DSC) Conference brings together educators to explore innovative approaches to teaching and learning data science.
This one-day conference showcases emerging practices in data science education, highlights successful student and faculty initiatives, and fosters collaboration within and between all tiers of K-16 education. Participants engage in meaningful conversations about curriculum innovation, student success, workforce development, and the future of data science education.
The conference is supported by California Education Learning Lab.
Conference Goals
- Showcase innovative approaches to teaching data science
- Highlight successful student experiences and pathways in data science
- Explore strategies for developing and sustaining data science programs
- Strengthen transfer, articulation, and workforce pathways in data science
- Build and sustain a regional Community of Data Science Learners
Previous Conferences
DSC 2024: New Programs & New Responsibilities
DSC 2025: From Insight to Impact: Adapting and Transforming the Landscape of Data Science Pathways
Project PIPE-LINE is a collaboration between California State University Fullerton, Riverside City College, Rio Hondo College, and University of California Irvine. Funded by California Learning Lab: Building Critical Mass for Data Science