Data Science
The goal of the Data Science Program is to provide comprehensive training in this growing interdisciplinary field. Through courses in statistics, computing, and applied domains (e.g. government, environmental science, sociology), students explore the societal impact of data science and such ethical concerns as privacy rights and data validity.
About the Major
There is accelerating demand in academic, government, and business settings for those with the quantitative, statistical, and technological expertise to collect and analyze large data sets.
A concentration in data science allows students to engage with statistical methods, algorithms, data structures, and machine learning to gain a critical understanding of the data life cycle and analysis.
Students Will Learn To:
- Gain proficiency in the data life cycle: creation, curation, documentation, analysis, and communication.
- Apply data science tools to real world problems and produce well documented and reproducible analyses.
- Understand the social and ethical impact of the tools used in data science.
Meet Our Faculty
Chinthaka Kuruwita
Associate Professor of Statistics, Director of Data Science
nonparametric density estimation and quantile regression models
Mark Bailey
Chair, the Robert and Pamela (Craig) Delaney Professor of Computer Science
the boundary between hardware and software, including program optimization, embedded systems, computer architecture and computer security
uncertainty quantification, probabilistic modeling and simulation, mathematical biology, and high-performance computing
environmental data science, ecohydrology, ecology, and geospatial analysis
Explore Hamilton Stories
Tracking Climate Change Through AI
Artificial intelligence and climate change are among the very foremost hot-button issues of today. This summer, a project by Adam Koplik ’25 and Assistant Professor of Environmental Studies Heather Kropp is using one to explore the other—by employing machine learning to measure vegetation change in the Arctic.
Senior Theses Dig Deep, Demonstrate Knowledge Gained
Sean Kondracki ’24 analyzed election data from 2012, 2016, and 2020 to determine and model patterns in non-voter activity for his data science senior project.
Contact
Department Name
Data Science Department
Contact Name
Chinthaka Kuruwita, Program Director
Clinton, NY 13323
