Data Science Minor

Data science is an interdisciplinary field of study that focuses on understanding, processing, interpreting, visualizing, and communicating data.

Minor Requirements

The minor comprises three core courses (a statistics course from any department, DS 256, and DS 325), and three electives.

  • One course in statistics
  • DS 256 Data Science Programming
  • DS 325 Applied Data Science
  • Three electives

Core Courses

Approved Statistics Courses
Course Number Course Title Prerequisites
BIO 260 Biostatistics Bio 112
ECON 241 Introductory Economics and Business Statistics ECON 103 and 104, and one of the following: Math 105-106, 111 or equivalent; or department permission
HS 232 Statistics for Health Sciences None
MATH 107 Applied Statistics None
MATH 353 Probability and Statistics Math 211 & Math 212 with a C- or better
MGT 235 Statistical Methods None
POL 215 Methods of Political Science Completion of Pol 101, 102, 103, or 104 and sophomore status or above
PSYCH 205 Introduction to Statistics PSYCH 101 and Psychology major
SOC 299 Data Analysis and Statistics 1 100-level Sociology course and 1 200-level Sociology course

DS 256 Data Science Programming

Data scientists apply methods from statistics, data analysis, computer science, and machine learning in order to gain insight from data. In Data Science Programming, we focus on developing the programming and machine learning skills necessary to gain such insight. Through experiential learning, we equip students with the fundamental computer problem-solving skills and tools to clean raw data, engineer data features, build statistical and machine learning models, predict unknown values and/or discern patterns, and present data insights. No prerequisites.

DS 325 Applied Data Science

Advanced treatment of data science concepts. Through a series of case studies, students explore datasets from a variety of domains and extract meaningful information and insights using mathematical, computational, and other scientific methods and algorithms. Topics include the fundamental algorithms of data science: regression, decision trees, support vector machines, clustering, and neural networks. Through a semester-long project, students demonstrate knowledge of fundamental data science concepts and ability to interpret and communicate effectively the results of the analysis. Prerequisites: DS 256: Data Science Programming and an approved statistics course.

Elective Courses

Students must take three approved elective courses. At least one elective must be taken outside the student’s major (s), and only one elective can be at the 100-level. One possible elective is the newly approved DS 150 Data Science and Society, but we offer many other courses that fulfill the elective requirement.

DS 150: Data Science and Society

This course introduces students to data science and research design. This course is divided into two parts. During the first half of the semester, students will be introduced to theories of science and how systematic and falsifiable analysis applies to a wide variety of fields of study. During the second half of the semester, students will be introduced to data management, statistical and computer programming software, and econometrics.

Approved Elective Courses
Course Number Course Title Prerequisites
ARTS 160 Introduction to Digital Media None
BIO 251/CS 251 Introduction to Bioinformatics BIO 112
BIO 315 Molecular and Genome Evolution BIO 211
CS 360 Principles of Database Systems CS 216
CS 371 Introduction to Artificial Intelligence CS 216
DS 150 Data Science and Society None
DS 220 Cultural Analytics Any 100-level course in SOC or CIMS; MUS_CLAS-213; OR any 200-level course in ENG or foreign languages and literatures; OR any gateway course for area, ethnic, group, or global studies majors (e.g. LAS 145).
DS 265 “Just” Data Previous credit or concurrent registration in one of: CS 107 or 111; OR Math 107 or equivalent; OR DS 256.
ECON 350 Econometrics ECON 241, 243, and 245
ECON 352 Advanced Econometrics ECON 350, plus one other 300-level ECON course
ES 230 Introduction to Geographic Information Systems ES 196 or permission of instructor
ES 304 Landscape Ecology ES 211 and ES 230
ES 363 Remote Sensing ES 230 or permission of instructor
FYS 162 Math and Voting First year students only
MATH 342 Applied Linear Algebra MATH 212 with a C- or better
MATH 353* Probability and Statistics MATH 211 and MATH 212 with a C- or better
MATH 362 Operations Research None
MATH 363 Wavelets and Their Applications MATH 212 with a C- or better
MGT 301 Research Methods MGT 235
MGT 303 Systems Thinking MGT 235 and MGT 275
MGT 321 Topics in Operations Management MGT 235 or declared business minor that has completed statistics requirement
MGT 395 Organizational Ethics Jr or Sr status
PHIL 109 Wrong Science, Bad Science, Pseudo Science None
PHIL 211 Logic 100 level philosophy course or permission of instructor
PHIL 253 Philosophy of Technology 100 level philosophy course or permission of instructor
PHYS 335 Computational Methods in Physics Jr or Sr status and instructor permission
PHYS 350 Observational Astronomy PHYS 211, PHYS 110, or instructor permission
PSYCH 305 Experimental Methods PSYCH 205

* For the Data Science Minor, Math 353 can count as either the Statistics course or as an elective. It cannot count as both.

Elective Courses through Affiliated Study Abroad Programs

Many off campus study programs offer courses that meet DS minor requirements, including:

  • Lancaster University, England offers a variety of undergraduate courses in data science across several departments.
  • CET Shanghai, China offers a full undergraduate program of courses and internship opportunities in data science.
  • DIS in Copenhagen, Denmark offers several courses that would support the Data Science minor including Computational Analysis of Big Data and Econometrics.
  • American University in Cairo, Egypt offers a BSc in Data Science and a full curriculum taught in English.
  •