Study Data Science
Data Science is the fastest growing major at UW-Madison. Whether you are interested in a data science career, course, or workshop, opportunities abound here! Learn about undergraduate majors, graduate programs, the data science certificate, workshops, and internships and careers.
Explore Campus Resources
Data science has applications in all disciplines, and Data Science @ UW is your connection to data science institutes, centers, and programs across the UW-Madison campus. It’s also the place to find research funding and resources, coding meetups, seminars and events, data science faculty and communities of practice, student organizations, and more!
Collaborate With Us
Data science innovation at UW-Madison furthers the Wisconsin Idea by fueling discovery and economic development in all corners of the state and beyond. We are committed to fostering an inclusive culture in data science. Campus, industry, and community partners can benefit from our data science services.
Data Science Events
- September
- September 10Introducing ML+X Nexus – Your Gateway to Collaborative Machine Learning and AI Resources!Machine Learning Beyond Traditional CS Fields12:00 PM, Orchard View Room, Discovery Building
Also offered online - September 10Graduate Applied Math SeminarMartin Guerra - Introduction to diffusion models: theory and application4:00 PM, B223 Van Vleck Hall
- September 11
News and Announcements
Julia Workshop for Statistics Research
Join the Statistics Department for the Julia Workshop for Statistics Research, Thursdays 12-1pm in MSC 1210, September 19 - October 24. The goal for this six-week workshop is to highlight the main features that make Julia an attractive option for data science programmers.
GeoMachina: What Designing Artificial GIS Analysts Teaches Us About Place Representation
This Geospatial Data Science Seminar with Dr. Krzysztof Janowicz will report on conceptual lessons learned in designing and benchmarking autonomous, artificial GIS analysts, provide a brief overview of place representation paradigms studied over the past 20 years, and discuss the potential of neuro-symbolic (hybrid) AI to advance our field.
How Open Source is Fostering Innovation in AI
The Open Source Program Office (OSPO) and the Data Science Institute (DSI) invite you to our upcoming Innovate Week event, How Open Source is Fostering Innovation in AI, Thursday, September 26, 2024. The presentations and panel discussion will explore the transformative role of open source technologies in advancing the AI landscape.
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Faces of Data Science
“UW-Madison’s data science degree programs are successful because we are using math for a purpose. Data science has in the background all these mathematical ideas and models that help you make a conclusion about data. Students might not be aware of all the models they are using, but they are there, under the hood.”
Alejandra Quintos
Assistant Professor, Department of Statistics; Visiting Professor, Universidad Nacional Autónoma de Mexico (UNAM); Nellie McKay Fellow
Alejandra Quintos always liked math. As a young person in Mexico, however, she didn’t know any mathematicians or receive encouragement to pursue a degree in this field. She earned her undergraduate degree in actuarial science, hoping it would open doors to a career in the U.S. During a summer research opportunity at Cornell, mathematics professor Steven Strogatz encouraged her to pursue a Ph.D. in the U.S., and she went on to earn her doctorate in statistics from Columbia.
Quintos applies her training in probability and theoretical statistics to solve problems in finance. One of her interests is microlending, where banks provide loans to small groups of low-income borrowers with no credit history. Through mathematical modeling, she confirmed an ideal group size of five people for microloan repayment. She is using reinforcement learning to glean new insights from microlending data, helping financial institutions optimize loan amounts and set fair interest rates.
Teaching and transmitting knowledge are what Quintos loves about her work. She values communicating with both students and lay audiences, and she relishes moments of insight when her students understand something complicated or see a problem in a new way.