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Data Science Bootcamps

Academic Year Data Science Bootcamps

Explore Data Science and AI During the School Year

UVA Academic Year Data Science Bootcamps introduce young learners to data science and artificial intelligence through programs offered during the school year at the University of Virginia in Charlottesville.

Programs are designed for students with no prior data science experience and use hands-on activities to introduce foundational data science and AI concepts.

Questions? Email Emma Cox at emc2@virginia.edu 

Fall Break Data Science Bootcamp: Introduction to Coding (Python)

Intended for both middle and high school students with no previous coding experience. This camp will cover the basics of Python to equip participants with the foundational knowledge required to begin their coding journey. Those with previous experience coding in other languages, such as Java, are still eligible to participate. 

  • Dates: November 2-3, 2026
  • Time: 9 am - 3 pm daily 
  • Cost: $150
  • Location: UVA School of Data Science, 1919 Ivy Road, Charlottesville, VA 22903
  • Register for the fall here

Spring Break Data Science Bootcamp: Policy & Ethics

Intended for students interested in exploring how data science, artificial intelligence, and technology impact society. Through engaging discussions, hands-on activities, and real-world case studies, participants will examine topics such as privacy, fairness, bias, governance, and the responsible use of technology. No prior coding or technical experience is required.

Middle School

High School

What Do Students Learn?

Students build foundational data science and AI literacy while learning to ask questions, recognize patterns, interpret information, and think critically about technology.

Students may explore how machines learn from data, investigate how training data and bias can affect AI systems, discuss AI use in real-world settings, and learn the basics of generative AI and prompting.

The inaugural class also explored data through art. Students collected and analyzed their own data and transformed a group dataset about play into a three-dimensional collaborative installation.

Topics and activities may include:

  • Data collection and analysis
  • Artificial intelligence and machine learning
  • Generative AI and prompting
  • Training data and bias
  • AI ethics and responsible technology
  • Data visualization and storytelling
  • Creative and collaborative problem-solving