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Enabling Computational Education
The Center for Computational Thinking (CCT) enables computational education at Duke to ensure that every student, regardless of field of study, is prepared for the digital 21st century. Through partnerships with faculty, programs, and departments spanning a wide range of disciplines including data science, cybersecurity, policy, and ethics, we bring computational learning experiences and opportunities to the Duke community and beyond.
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CCT/UseR Conference August 8-10, 2025
Join us for a weekend of learning and networking this August! Read more about the conference.
Learning opportunities & student experiences
For all our videos, visit our YouTube channel.
#rstats Projects
In this series, Mine Çetinkaya-Rundel, Ph.D. (Professor of the Practice of Statistical Science, Duke University) teams up with an undergraduate student to explore and visualize four different datasets to answer questions of mutual interest and showcase the process of doing data science with R, collaboratively.
Student Experiences
Explore the wide variety of fascinating projects Duke students have engaged in, at every level - undergraduate, masters, and Ph.D. Watch and be inspired!
Generative AI and Image Production
How do AI image making methods function? And how does the practice of these methods fit into visual culture production? This presentation includes technical and cultural image making topics to present a starting point for critical generative AI image making. Presented by Augustus Wendell, Duke University Assistant Professor of the Practice of Art, Art History, and Visual Studies, and Matthew Kenney, Co-Founder and CTO of Aspect Labs.
Our partners
The CCT works with partner programs and organizations across Duke to deliver learning opportunities that align with our vision of preparing all Duke students -- regardless of field of study -- for the digital twenty-first century.
- AI Health
- Bass Connections
- Center for Data and Visualization Sciences (CDVS)
- Code+ Summer Program
- Computational Media, Arts & Cultures (CMAC)
- CS+ Summer Program
- +DataScience (+DS)
- Data+ Summer Program
- DTech
- Duke Graduate School
- Duke Institute for Brain Sciences (DIBS)
- Duke Learning Innovation
- Duke University Libraries
- Heureka Labs
- Math+ Summer Program
- Office of Information Technology - including Innovation Co-Lab
- Office of the Provost
- Pratt School of Engineering
- Rhodes Information Initiative at Duke (iiD)
- Sanford School of Public Policy
- School of Medicine - including Biostatistics & Bioinformatics
- Science & Society - including Digital Intelligence (DQ) Certificate Program
- Tech Policy@Sanford
- Trinity College of Arts & Sciences - including Art, Art History, & Visual Studies; Computational Media, Arts & Cultures; Computer Science; Economics; English; Mathematics; and Statistical Science
Four pillars support everything we do
The four pillars of the CCT represent the strategic priorities and areas of focus for the center. Developed by executive leadership and faculty members, the pillars provide a roadmap for initiatives and new development.
Every student in computing majors/minors can pursue flexible, personalized pathways through an interdisciplinary curriculum marrying computing, liberal arts, and societal grand challenges that emphasizes experiential and team learning. Learn more about Pillar 1.
Every major, minor, and certificate program can explore pedagogical innovation arising from the infusion of computational thinking into its curriculum. Learn more about Pillar 2.
Any student can explore a range of computational topics via co-curricular opportunities ranging from bite-sized courses and workshops to summer programs and internships. Learn more about Pillar 3.
Every student gains the computational literacy that enables them to understand the impact of technology, to harness its power in their life, and to be a responsible citizen in our digital society. Learn more about Pillar 4.
The CCT is connecting existing resources at Duke — and responding to gaps in our current offerings — to ensure all students and faculty have the opportunity to bring [computational] approaches to their studies and their research.
Sally Kornbluth, former Duke University Provost