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, 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
Digital Hamilton: Learning Data Science Across Disciplines
A math major with an environmental studies minor, Rachel Pike ’21 saw data science as a natural combination of her interests, and a new course gave her a chance to confirm that. She enrolled in ENVST 206 Environmental Data Science.
Sweet ’03 Shares Career Path in Data Science
In her talk “Policy, Translation, Estimation, and Inference: When Big Data Isn’t Enough,” Shauna Sweet ’03 returned to campus to discuss her career experience in applied analytics.
Contact
Department Name
Data Science Department
Contact Name
Chinthaka Kuruwita, Program Director
Clinton, NY 13323
