Data Science (DATA)

DATA Courses

DATA-113 Introduction to Data Science

Fall and Spring. Credits: 4

Data scientists answer questions with scientific and social relevance using statistical theory and computation. We will discuss elementary topics in statistics and learn how to write code (in Python) to visualize data and perform simulations. We will use these tools to answer questions about real data sets. We will also explore ethical issues faced by data scientists today.

Applies to requirement(s): Math Sciences

DATA-225 Topics in Data Science

DATA-225AR Topics in Data Science 'Ethics and Artificial Intelligence'

Spring. Credits: 4

Artificially intelligent technologies are prominent features of modern life -- as are ethical concerns about their programming and use. In this class we will use the tools of philosophy to explore and critically evaluate ethical issues raised by current and future AI technologies. Topics may include issues of privacy and transparency in online data collection, concerns about social justice in the use of algorithms in areas like hiring and criminal justice, and the goals of developing general versus special purpose AI. We will also look at ethics for AI: the nature of AI "minds," the possibility of creating more ethical AI systems, and when and if AIs themselves might deserve moral rights.

Crosslisted as: PHIL-260AR, EOS-299AR
Applies to requirement(s): Humanities

DATA-225DH Topics in Data Science: 'Introduction to Digital Humanities'

Spring. Credits: 4

This class is an interdisciplinary course that examines the application of computational tools and methodologies to humanities research, with a strong emphasis on practical Python programming. It covers key topics such as image processing, data visualization, and statistical analysis applied in various domains, including history, archaeology, and the arts. Students engage with diverse case studies and projects, employing computational and statistical techniques to analyze and interpret complex real-world datasets. The course also critically explores methodological challenges in digital humanities, including issues related to sparse data, noisy contexts, and the inherent limits of interpretation.

Applies to requirement(s): Math Sciences
Prereq: DATA-113 (or COMSC-151 and STAT-140) or equivalent familiarity with Python and statistics. Contact the instructor if needed.

DATA-295 Independent Study

Fall and Spring. Credits: 1 - 4

Restrictions: Contact instructor for independent study declaration form and signatures.
Instructor permission required.

DATA-350 Advanced Topics in Data Science:

DATA-350TE Advanced Topics in Data Science: 'Technology, Ethics, and Public Policy'

Not Scheduled for This Year. Credits: 4

In this course, we study the most pressing ethical concerns relating to emerging technology and envision novel policy solutions to address them. Existing regulatory and policy instruments are often unable to provide sufficient oversight for emerging technology. Can legal anti-discrimination doctrine address biased algorithmic decision-making systems? How does generative artificial intelligence challenge traditional ways of thinking about intellectual property? Do we have rights over the personal data that private firms collect about us? We examine these gaps in the context of contemporary regulatory proposals on national, multinational, and international scales.

Crosslisted as: PHIL-350TE
Applies to requirement(s): Humanities
Other Attribute(s): Writing-Intensive
Prereq: 8 credits in Philosophy.

DATA-390 Research and Topics in Data Science

Fall. Credits: 4

This seminar provides an opportunity for students from all disciplines to do guided research using data science tools in a research project of their choice. Students will develop an understanding of the full pipeline of successful data science research by selecting a topic, identifying relevant datasets, designing research methods, conducting in-depth analyses, deriving meaningful conclusions, and submitting a final report. Opportunities for students to present their work and review journal articles create a scaffolded approach. Past project topics include geology, music, demographics, art, economics, government, religion, transportation, and law.

Applies to requirement(s): Math Sciences
Prereq: STAT-242 and COMSC-205, or a 300-level class in Statistics or Computer Science.

DATA-395 Independent Study

Fall and Spring. Credits: 1 - 8

Restrictions: Contact instructor for independent study declaration form and signatures.
Instructor permission required.

DATA-395P Independent Study w/Practicum

Fall and Spring. Credits: 1 - 8

Restrictions: Contact instructor for independent study declaration form and signatures.
Instructor permission required.

Required Core Courses for the Data Science Major

Computer Science
COMSC-151Introduction to Computational Problem Solving4
COMSC-205Data Structures4
COMSC-335Machine Learning4
Mathematics
MATH-211Linear Algebra4
Statistics
STAT-140Introduction to the Ideas and Applications of Statistics4
STAT-242Intermediate Statistics4
STAT-340Applied Regression Methods4

Elective Courses for the Data Science Major

Biological Sciences
BIOL-223Ecology with Laboratory4
BIOL-234Biostatistics with Laboratory4
BIOL-350GETopics in Biological Sciences: 'Genomics and Bioinformatics with Laboratory'4
Computer Science
COMSC-235Applications of Machine Learning4
COMSC-312Algorithms4
COMSC-334Artificial Intelligence4
COMSC-335Machine Learning4
COMSC-341CDTopics: 'Causal Inference for Data Science'4
COMSC-341NLTopics: 'Natural Language Processing'4
COMSC-341TETopics: 'Text Technologies for Data Science'4
Data Science
DATA-113Introduction to Data Science4
DATA-225ARTopics in Data Science 'Ethics and Artificial Intelligence'4
DATA-350TEAdvanced Topics in Data Science: 'Technology, Ethics, and Public Policy'4
DATA-390Research and Topics in Data Science4
Economics
ECON-220Introduction to Econometrics4
ECON-320Econometrics4
Entrepreneurship, Orgs & Soc
EOS-299ARTopic: 'Ethics and Artificial Intelligence'4
Geography
GEOG-205Mapping and Spatial Analysis4
GEOG-210GIS for the Social Sciences and Humanities4
Mathematics
MATH-339PTTopics in Applied Mathematics: 'Optimization'4
MATH-339SPTopics in Applied Mathematics: 'Stochastic Processes'4
MATH-342Probability4
Philosophy
PHIL-260ARTopics in Applied Philosophy: 'Ethics and Artificial Intelligence'4
PHIL-350TETopics in Philosophy: 'Technology, Ethics, and Public Policy'4
Politics
POLIT-387ECAdvanced Topics in Politics: 'U.S. Elections'4
Psychology
PSYCH-326CPLaboratory in Personality and Abnormal Psychology: 'Advanced Statistics in Clinical Psychology'4
Sociology
SOCI-216TXSpecial Topics in Sociology: 'Text as Data I: From Qualitative to Quantitative Text Analysis'4
SOCI-316TXSpecial Topics in Sociology: 'Text as Data II: Computational Text Analysis for the Social Sciences'4
Statistics
STAT-244MPIntermediate Topics in Statistics: 'Survey Sampling'4
STAT-244NFIntermediate Topics in Statistics: 'Infectious Disease Modeling'4
STAT-244NPIntermediate Topics in Statistics: 'Nonparametric Statistics'4
STAT-244SCIntermediate Topics in Statistics: 'Computational Statistics'4
STAT-331Design of Experiments4
STAT-340Applied Regression Methods4
STAT-343Mathematical Statistics4
STAT-344NDSeminar in Statistics and Scientific Research: 'Analysis of Neural Data'4
STAT-344TMSeminar in Statistics and Scientific Research: 'Time Series Analysis'4
STAT-351Bayesian Statistics4