¹û¶³´«Ã½

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
K. Mulder, A. Shaus, L. Tupper

DATA-225 Topics in Data Science:

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

Not Scheduled for This Year. 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
L. Sizer

DATA-295 Independent Study

Fall and Spring. Credits: 1 - 4

The department
Instructor permission required.

DATA-350 Advanced Topics in Data Science:

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

Spring. 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
A. Ali
Prereq: 8 credits in Philosophy.

DATA-390 Data Science Capstone

Fall and Spring. Credits: 4

The Capstone is a research seminar that empowers students to design and execute a significant data science research project. Through group review of journal articles and targeted lectures, students will develop a thorough understanding of each of the components of a successful research project including defining their research question, conducting a literature review, identifying an appropriate data set, designing and implementing a defensible methodology, and presenting and interpreting their results in text, tables, and figures. There will be frequent opportunities for students to present their work, and their capstone will culminate in a written report. Concurrently, students will read and discuss several case studies that address issues of ethics involved with the collection, treatment, and analysis of data.

Applies to requirement(s): Math Sciences
K. Mulder, A. Shaus
Prereq: STAT-340 or COMSC-335. STAT-340 or COMSC-335 may be taken concurrently (contact instructor for permission).

DATA-395 Independent Study

Fall and Spring. Credits: 1 - 8

The department
Instructor permission required.

DATA-395P Independent Study w/Practicum

Fall and Spring. Credits: 1 - 8

The department
Instructor permission required.