Data Science

Eleanor Townsley, Nexus director

Amber Douglas, track chair

Martha Hoopes, track chair


217G Dwight Hall
413-538-3010
https://www.mtholyoke.edu/acad/nexus/data-science

Overview and Contact Information

Data Science is an emerging discipline that integrates computational, programming, and statistical skills in applications across a range of fields. This discipline uses different types of data to create an accessible narrative and helps pose new questions, identify patterns, visualize trends, and make predictions using new techniques. Data scientists have the potential to offer novel insights, expand our ability to ask questions that push the limits of our understanding, and harness the creativity, critical thinking, and communication skills that form the core of a liberal arts education. The vast quantities of data created by modern life make Data Science possible but also drive the need for an approach to the discipline that takes privacy and other ethical considerations seriously.

See Also

Faculty

This area of study is administered by the Data Science committee:

Valerie Barr, Jean E. Sammet Professor of Computer Science

Andrea Foulkes, Professor of Mathematics and Statistics

Janice Gifford, Professor of Statistics

Martha Hoopes, Professor of Biological Sciences, Teaching Fall Only

Jessica Sidman, Professor of Mathematics on the John Stewart Kennedy Foundation, Teaching Spring Only

Eleanor Townsley, Andrew W. Mellon Professor of Sociology and Director of Nexus

Amber Douglas, Associate Professor of Psychology and Education; Director of Student Success Initiatives

Barbara Lerner, Associate Professor of Computer Science

Katherine Schmeiser, Associate Professor of Economics, On Leave 2017-2018

Steven Schmeiser, Associate Professor of Economics, Teaching Fall Only

Dylan Shepardson, Associate Professor of Mathematics

Kate Singer, Associate Professor of English

Mara Breen, Assistant Professor of Psychology and Education

KC Haydon, Assistant Professor of Psychology and Education

Heather Pon-Barry, Clare Boothe Luce Assistant Professor of Computer Science, On Leave 2017-2018

Andy Reiter, Assistant Professor of Politics and International Relations

Timothy Malacarne, Visiting Assistant Professor of Data Science

Daniel Sheldon, Five College Assistant Professor of Computer Science

Eitan Mendelowitz, Visiting Assistant Professor of Data Science

Samuel Tuttle, Visiting Assistant Professor of Data Science

Requirements for the Nexus

A minimum of 18 credits:

Four 4-credit courses, of which:16
one must be in statistics at the 200 level or higher, from the list of courses approved for this Nexus
one must be in computer science at the 200 level or higher, from the list of courses approved for this Nexus
one must be in an application area (e.g., biology, economics, English, psychology, sociology) at the 200 level or higher, from the list of courses approved for this Nexus
one is an elective course that demonstrates an interest in data science and that may be taken at the 100 level and must be taken before the internship
Note: at least one of these four courses must be an approved 300-level capstone course that goes into depth in statistics, computer science, or a data science application area. Appropriate courses include: COMSC-335, ECON-320, SOCI-316NT, STAT-340 or STAT-344 2
Completion of the UAF application stages 1 and 2 1
A substantive internship
COLL-211Reflecting Back: Connecting Internship and Research to your Liberal Arts Education2
A presentation at LEAP Symposium
Total Credits18
1

 Or a fifth class with approval of the track chair

2

Other capstone courses would require prior approval from the Nexus committee

Additional Specifications

  • In one of the four courses for this Nexus, students must work intimately with data to explore, visualize, contextualize, and present conclusions.
  • The sequence of a Nexus is part of what makes it unique. Students must complete at least one of their four courses towards the Nexus and UAF application stages 1 and 2 before the internship or research project. COLL-211 is taken after the internship or research project and culminates in a presentation at LEAP Symposium.

Courses Counting toward the Nexus

Courses other than those listed below may count toward the Nexus. Students should consult the Nexus track chair for consideration of courses not on the list.

ASTR-226Cosmology4
ASTR-228Astrophysics I: Stars and Galaxies4
BIOL-223Ecology4
BIOL-234Biostatistics4
COMSC-201Advanced Problem-Solving and Object-Oriented Programming4
COMSC-211Data Structures4
COMSC-243EMTopic: 'Embodied Interaction'4
COMSC-311Theory of Computation4
COMSC-312Algorithms4
COMSC-334Artificial Intelligence4
COMSC-335Machine Learning4
COMSC-336Intelligent Information Retrieval4
COMSC-341NLTopics: 'Natural Language Processing'4
COMSC-341SPTopics: 'Computer Security & Privacy'4
COMSC-343Programming Language Design and Implementation4
ECON-220Introduction to Econometrics4
ECON-320Econometrics4
ECON-349DTAdvanced Topics in Economics: 'Data Science and Economics'4
ENVST-200Environmental Science4
GEOG-205Mapping and Spatial Analysis4
GEOG-210GIS for the Social Sciences and Humanities4
GEOG-320Research with Geospatial Technologies4
GEOL-247Environmental Modeling & Statistics4
HIST-257Research Methods in History, Environmental Change, and Public Health4
IR-200Research Methods4
MATH-211Linear Algebra4
MATH-301Real Analysis4
MATH-342Probability4
PSYCH-201Statistics4
PSYCH-204Research Methods in Psychology4
PSYCH-310APLaboratory in Social Psychology: 'Community-Based Participatory Action Research'4
PSYCH-326BHLaboratory in Personality and Abnormal Psychology: 'Behavioral Methods for Social and Intergroup Psychology'4
PSYCH-326PRLaboratory in Personality and Abnormal Psychology: 'Personality Research'4
PSYCH-330RDLab in Developmental Psychology: 'Laboratory in Romantic Development: Observational Coding Methodology'4
SOCI-225Survey Research and Data Analysis4
SOCI-316NTSpecial Topics in Sociology: 'Social Network Analysis: Analyzing Who You Know and How It Matters'4
STAT-240Elementary Data Analysis and Experimental Design4
STAT-241Methods in Data Science4
STAT-242Intermediate Statistics4
STAT-340Applied Regression Methods4
STAT-343Mathematical Statistics4