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

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

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

Mara Breen, Associate Professor of Psychology and Education, Teaching Fall Only

KC Haydon, Associate Professor of Psychology and Education

Barbara Lerner, Associate Professor of Computer Science, Teaching Spring Only

Andy Reiter, Associate Professor of Politics and International Relations, Teaching Spring Only

Katherine Schmeiser, Associate Professor of Economics

Steven Schmeiser, Associate Professor of Economics

Dylan Shepardson, Associate Professor of Mathematics, On Leave 2018-2019

Kate Singer, Associate Professor of English

Heather Pon-Barry, Clare Boothe Luce Assistant Professor of Computer Science

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

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.

Astronomy
ASTR-226Cosmology4
ASTR-228Astrophysics I: Stars and Galaxies4
Biological Sciences
BIOL-223Ecology4
BIOL-321SCConference Course: 'Landscape Ecology'4
Computer Science
COMSC-100An Introduction to Computer Science4
COMSC-103Networks4
COMSC-106Fundamentals of Applied Computing4
COMSC-151DSIntroduction to Computational Problem Solving: 'Data Science'4
COMSC-201Advanced Problem-Solving and Elementary Data Structures4
COMSC-205Data Structures4
COMSC-211Advanced Data 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
Economics
ECON-220Introduction to Econometrics4
ECON-320Econometrics4
Environmental Studies
ENVST-200Environmental Science4
Geography
GEOG-205Mapping and Spatial Analysis4
GEOG-210GIS for the Social Sciences and Humanities4
GEOG-320Research with Geospatial Technologies4
GEOG-342SCSeminar in Geography: ''Landscape Ecology'4
Geology
GEOL-131Introduction to Hydrology: A Data Perspective4
GEOL-247Environmental Modeling & Statistics4
GEOL-342SCSeminar in Geology: 'Landscape Ecology'4
International Relations
IR-200Research Methods4
Mathematics
MATH-211Linear Algebra4
MATH-301Real Analysis4
MATH-342Probability4
Psychology
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-330RDLab in Developmental Psychology: 'Laboratory in Romantic Development: Observational Coding Methodology'4
Sociology
SOCI-225Social Science Research and Data Analysis4
SOCI-316NTSpecial Topics in Sociology: 'Social Network Analysis: Analyzing Who You Know and How It Matters'4
Statistics
STAT-240Elementary Data Analysis and Experimental Design4
STAT-241Methods in Data Science4
STAT-242Intermediate Statistics4
STAT-340Applied Regression Methods4
STAT-343Mathematical Statistics4
STAT-344SMSeminar in Statistics and Scientific Research: 'Survey Sampling'4