Two-Year College Data Science Initiative (TYCDSI)

Level 2 Support

Two-Year College Data Science Initiative (TYCDSI) 2.0 is an AMATYC project to provide a workshop to provide technical and pedagogical training to two-year college faculty teaching data science at their institutions. It is funded by the NSF (DUE 2508047).

What: Workshop to teach technical and pedagogical topics for teachers of data science courses.

When: June 11-13, 2026

Where: College of the Canyons, Santa Clarita, California

What you will learn:

Develop skills to create data visualizations

Programming in r, Python, and Tableau

Explore version control sites such as github

Discuss attributes of a data science program

Establish a community of practice to support ongoing program development

Who can apply: Any two-year college faculty interested in creating a data science program

Deadline for applications: Monday, Mach 2, 2026 by midnight
Selected participants will be notified by March 30, 2026.

What participants agree to do: Share any questions or solutions on the community of practice

Applying for the workshop: Click here for application form

Travel expenses: Accepted participants will receive transportation allowance of up to $540 for travel, and up to 3 nights for accommodation. Breakfast, lunch, and dinner will be provided during the workshop. To receive funding for travel, participants must be US Citizens or Permanent Residents.

If you have any questions about the workshop, please contact: kathryn.kozak@amatyc.org.

Who is Presenting:

Hunter Glanz is an associate professor of statistics and data science at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in mathematics and a BS in statistics from Cal Poly, San Luis Obispo followed by an MA and PhD in statistics from Boston University. He maintains a passion for machine learning and statistical computing, and enjoys advancing education efforts in these areas. In particular, Cal Poly's courses in R, SAS, and Python give him the opportunity to connect students with exciting data science topics amidst a firm grounding in communication of statistical ideas. Hunter serves on numerous committees and organizations dedicated to delivering cutting-edge statistical and data science content to students and professionals alike, including being a founding board member of the California Alliance for Data Science Education. In particular, the ASA's DataFest event has been an extremely rewarding experience for the teams of Cal Poly students Hunter has had the pleasure of advising.

Rachel Saidi is a professor of Math, Statistics, and Data Science at Montgomery College and the Data Science Program Director. She created a number of courses for her college including Data Visualization and Communication, Biostatistics, and Applications in Linear Algebra. She collaborates with data science faculty and administrators and with organizations, industries, and local government representatives to provide various opportunities and experiences for students both during and after completing the certificate or degree. She was awarded Outstanding Faculty for Excellence in Teaching (2022) and the NISOD Award for Excellence (2023). She is currently the director for AMATYC's DataFest for Two-Year Colleges as well as a member of the ASA/AMATYC Joint Statistics and Data Science committee and the MAA CRAFTY committee.

Crystal Wiggins, D.B.A. is a Professor of Mathematics and STEM Department Chair at CT State Northwestern; and has taught in higher education for almost two decades, teaching courses ranging from basic math to statistics to advanced calculus as well as several data science courses. She spent two years researching and developing the first associate degree in data science in CT; the first cohort started in 2019. Crystal, and a small team of educators, host grant-funded professional development workshops nationwide for how to develop data science programs and learning instructional pedagogy for data science courses.

Solomon Russell, EdD, is Professor and Chair of the Computer Science Department at El Camino College in Los Angeles. He brings deep expertise in college and secondary curriculum development and in professional development for secondary teachers. His work focuses on expanding access to data science and computing for historically underserved students. He is the Principal Investigator on two current grant awards: the 2023 California Learning Lab's Data Science Grand Challenge, focused on faculty development in partnership with UC Berkeley, and a 2024 National Science Foundation grant focused on creating pathways for data science students at El Camino College.

Dr. Russell was appointed by the Governor in 2018 to the California Computer Science Strategic Implementation Advisory Panel, whose recommendations were adopted by the California State Board of Education. From 2012 to 2016, he served as the lead computer science curriculum developer and instructor for the SMASH Academy, a national STEM program for underrepresented high school students. He is an experienced keynote speaker and has been recognized with multiple teaching awards, including Computer Science Teacher of the Year from the El Camino ACM Chapter.

He completed his doctorate in education at the University of Southern California in 2023. His dissertation analyzes the curricular requirements for post-introductory community college data science education. As a faculty leader at El Camino, he led the creation of a new Certificate of Achievement in Data Science and continues to collaborate with statewide initiatives to transform the data science education landscape.

Grant Name

Principal Investigators

NSF #/ ID #

Grant Duration

Two-Year College Data Science Initiative (TYCDSI)

Kathryn Kozak
Ambika Silva
Rebecca Wong
Vinodh CHellamuthu

DUE 2402290

3/1/24 - 2/8/25

Abstract: This project aims to serve the national interest by engaging two-year college faculty in a workshop aimed at developing new data science associate degree pathways. By fostering collaboration and knowledge exchange, this project seeks to create a robust community of practice that will connect faculty working on such programs with one another and provide them with essential knowledge and skills needed to evolve this field of study. This endeavor will expand programming for students to pursue exciting new career paths in an emerging field. This initiative aligns seamlessly with the mission to advance the frontiers of knowledge, strengthen the Nation's scientific infrastructure, and cultivate a diverse, skilled workforce.

The Two-Year College Data Science Initiative project will support a workshop for two-year college faculty working to develop data science programs at their institutions. Workshop topics include forming interdisciplinary teams, examining exemplary data science curricula, establishing partnerships with baccalaureate institutions, researching regional workforce needs, and program evaluation. After the workshop, participants will continue to connect as a community of practice (CoP) within the American Mathematical Association of Two-Year Colleges (AMATYC). Participants will develop skills and confidence needed to create data science transfer programs at their institution, including a plan for program development, initiating articulation agreements with partner institutions, and plans for program development and evaluation. The NSF IUSE: Innovation in Two-Year College STEM Education (ITYC) Program seeks to accelerate the impact of and advance knowledge about emerging and evidence-based practices in undergraduate STEM education at two-year colleges.

Grant Name

Principal Investigators

NSF #/ ID #

Grant Duration

Two-Year College Data Science Initiative (TYCDSI)

Kathryn Kozak
Ambika Silva
Rebecca Wong
Vinodh CHellamuthu
Crystal Wiggins

DUE 2508047

8/1/25 - 7/31/26

Abstract: The Two-Year College Data Science Initiative (TYCDSI) Year 2 Workshop will provide the faculty from two year colleges with technical and pedagogical skills to teach the material needed in an associate degree in data science. Since data science is an emerging field, many two-year college instructors lack a strong background and experience in many of the tools used in this field. This workshop provides participants the opportunity to: 1) increase their proficiency in the use of several common data science technologies and 2) explore pedagogical best practices in data science education. At the conclusion of the workshop, participants in the TYCDSI will participate in a community of practice to provide ongoing support as they apply workshop content at their local institutions in developing their data science programs.

This workshop will build on the successful Two-Year College Data Science Initiative held in June 2024 (NSF DUE 2402290). That workshop focused on developing transfer programs in data science at two-year colleges. Evaluations from the 44 workshop participants were overwhelmingly positive, with over 90% of them rating the workshop as 5 on a scale from 1 to 5. However, workshop participants repeatedly mentioned that they needed professional development to further their own skills in data science, as they were developing their programs and looking at teaching this new curriculum. This project is designed to meet that need.

The American Mathematical Association of Two-Year Colleges (AMATYC) is committed to supporting its membership and two-year colleges in professional development to teach Data Science topics to students. As a result of the workshop, participants will:

Outcome 1: Develop technical skills to teach data science courses, such as an introduction to programming languages and data visualization tools

Outcome 2: Advance pedagogical skills needed to teach data science courses

Outcome 3: Explore resources for ongoing technical skill development post workshop

Outcome 4: Continue to develop the community of practice to support data science program development.